Systems That Learn: An Introduction to Learning Theory, Second Edition. Sanjay Jain, Daniel Osherson, James Royer, Arun Sharma. The MIT Press, 1999.
Addition Machines, Automatic Functions and Open Problems. Sanjay Jain, Xiaodong Jia, Ammar Fathin Sabilit and Frank Stephan. In Journal of Computer and System Science, Vol 136, pages 135--156, 2023.
String Compression in FA-presentable Structures. Sanjay Jain, Birzhan Moldagaliyev, Frank Stephan and Tien Dat Tran. In Acta Informatica, special issue on 70th birthday of Klaus-J\"orn Lange. Volume 59, pages 451--478, 2022.
A Computation Model with Automatic Functions and Relations as Primitive Operations. Ziyuan Gao, Sanjay Jain, Zeyong Li, Ammar Fathin Sabili and Frank Stephan. In Theoretical Computer Science, Volume 924, pages 94--116, 2022.
Deciding Parity Games in Quasipolynomial Time. Cristian S. Calude, Sanjay Jain, Bakhadyr Khoussainov, Wei Li and Frank Stephan. Accepted for Siam Journal of Computing. Special issue on STOC 2017.
Learners Based on Transducers. Sanjay Jain, Shao Ning Kuek, Eric Martin and Frank Stephan. Accepted for Information and Computation.
On the Amount of Nonconstructivity in Learning Formal Languages from Text. Sanjay Jain, Frank Stephan and Thomas Zeugmann. In Information and Computation, Volume 281, Article 104668, 2021.
Searching for Shortest and Least Programs. Cristian S. Calude, Sanjay Jain, Wolfgang Mekle and Frank Stephan. In Theoretical Computer Science, Volume 807, pages 114-127, 2020.
Reductions between Types of Numberings. Ian Herbert, Sanjay Jain, Steffen Lempp, Mustafa Manat and Frank Stephan. In Annals of Pure and Applied Logic, Volume 170, number 12, pages 1--25, 2019.
The Isomorphism problem for tree-automatic ordnals with addition. Sanjay Jain, Bakhadyr Khoussainov, Philipp Schlicht and Frank Stephan. In Information Processing Letters, Volume 149, pages 19--24, 2019.
An Ordered Approach to Solving Parity Games in Quasi-Polynomial Time and Quasi-Linear Space. John Fearnley, Sanjay Jain, Bart de Keijzer, Sven Schewe, Frank Stephan and Dominik Wojtczak. In International Journal on Software Tools for Technology Transfer, Volume 21, 325--349, 2019. Special issue on SPIN 2017.
Intrinsic Complexity of Partial Learning. Sanjay Jain and Efim Kinber. In Theoretical Computer Science, Volume 776, Pages 43--63, 2019.
The Complexity of Verbal Languages over Groups. Sanjay Jain, Alexei Miasnikov and Frank Stephan. In the Journal of Computer and System Sciences, Volume 101, Pages 68--85, 2019.
Learning Pattern Languages over Groups. Rupert Holzl, Sanjay Jain and Frank Stephan. Special Issue on ALT 2016. In Theoretical Computer Science, Volume 742, Pages 66--81, 2018.
Semiautomatic Structures Sanjay Jain, Bakhadyr Khoussainov, Frank Stephan, Dan Teng, and Siyuan Zou. In Theory of Computing Systems, 61(4), 1254--1287. Special Issue on Computability, Complexity and Randomness (CCR 2015).
Effectivity Questions for Kleene's Recursion Theorem. John Case, Sanjay Jain and Frank Stephan. In Theoretical Computer Science, Volume 733, Pages 55--70, 2018. Special issue on Learning and Complexity.
Finitely Generated Semiautomatic Groups. Sanjay Jain, Bakhadyr Khoussainov and Frank Stephan. In Computability, Volume 7, number 2--3, pages 273--287, 2018.
Enumerations including laconic enumerators. Sanjay Jain and Jason Teutsch. In Theoretical Computer Science, Volume 700, pages 89--95, 2017.
Automatic Learning from Positive Data and Negative Counterexamples. Sanjay Jain, Efim Kinber and Frank Stephan. In Information and Computation, Volume 255, pages 45--67, 2017.
Inductive Inference and Reverse Mathematics. Rupert Holzl, Sanjay Jain and Frank Stephan. In Annals of Pure and Applied Logic, Volume 167, pages 1242--1266, 2016.
Parallel Learning of Automatic Classes of Languages. Sanjay Jain and Efim Kinber. In Theoretical Computer Science, Vol 650, pages 25--44, 2016.
Closed Left-R.E. Sets. Sanjay Jain, Frank Stephan and Jason Teutsch. In Computability, Volume 6, number 1, pages 1--21, 2017.
Enlarging Learnable Classes. Sanjay Jain, Timo Kotzing and Frank Stephan. In Information and Computation, Vol 251, pages 194--207, 2016.
On the Role of Update Constraints and Text-Types in Iterative Learning. Sanjay Jain, Timo K\"otzing, Junqi Ma, and Frank Stephan. In Information and Computation, Vol 247, pages 152--168, 2016.
Tree-automatic scattered linear orders. Sanjay Jain, Bakhadyr Khoussainov, Philipp Schlicht and Frank Stephan. In Theoretical Computer Science, Vol 626, pages 83--96, 2016.
Deterministic Frequency Pushdown Automata. Cristian S. Calude, Rusins Freivalds, Sanjay Jain and Frank Stephan. The Journal of Universal Computer Science, Vol. 21, No. 12, pages 1563--1576, 2015.
Graphs realised by r.e. equivalence relations. Alexander Gavruskin, Sanjay Jain, Bakhadyr Khoussainov and Frank Stephan. In Annals of Pure and Applied Logic, Volume 165, pages 1263--1290, 2014.
Robust Learning of Automatic Classes of Languages. Sanjay Jain, Eric Martin and Frank Stephan. In Journal of Computer and System Sciences, Volume 80, pages 777-795, 2014.
Automatic Learners with Feedback Queries. John Case, Sanjay Jain, Yuh Shin Ong, Pavel Semukhin and Frank Stephan. In Journal of Computer and System Sciences, Volume 80, pages 806-820, 2014.
Automatic Functions, Linear Time and Learning. John Case, Sanjay Jain, Samuel Seah and Frank Stephan. In Logical Methods in Computer Science, Volume 9, issue 3, 2013.
Mind Change Speed-up for Learning Languages from Positive Data. Sanjay Jain and Efim Kinber. In Theoretical Computer Science, Volume 489--490, pages 37--47, 2013.
Learning and Classifying. Sanjay Jain, Eric Martin and Frank Stephan. In Theoretical Computer Science, Volume 482, pages 73--85, 2013.
Learning without coding. Sanjay Jain, Samuel E. Moelius III and Sandra Zilles. In Theoretical Computer Science, Volume 473, pages 124--148, 2013.
Learnability of Automatic Classes. Sanjay Jain, Qinglong Luo and Frank Stephan. In Journal of Computer and System Sciences, Volume 78, issue 6, Pages 1910--1927, 2012. Special issue on LATA 2010.
Automatic Learning of Subclasses of Pattern Languages. John Case, Sanjay Jain, Trong Dao Le, Yuh Shin Ong, Pavel Semukhin, and Frank Stephan. In Information and Comptation, Volume 218, pages 17--35, 2012.
Learning with ordinal-bounded memory from Positive Data. Lorenzo Carlucci, Sanjay Jain and Frank Stephan. In Journal of Computer and System Sciences, Volume 78, Number 5, Pages 1623--1636, 2012.
Rice and Rice-Shapiro Theorems for transfinite correction grammars. John Case and Sanjay Jain. In Mathematical Logic Quarterly, Volume 57, Number 5, pages 504--516, 2011.
Iterative Learning from Texts and Counterexamples Using Additional Information. Sanjay Jain and Efim Kinber. In Machine Learning, Volume 84, Number 3, pages 291--333, 2011.
Hypothesis Spaces for Learning. Sanjay Jain. In Information and Computation, Volume 209, Number 3, pages 513--527, 2011. Special Issue 3rd International Conference on Language and Automata Theory and Applications (LATA 2009).
Uncountable Automatic Classes and Learning. Sanjay Jain, Qinglong Luo, Pavel Semukhin and Frank Stephan. In Theoretical Computer Science, Volume 412, number 19, pages 1805--1820, 2011. Special Issue on Algorithmic Learning Theory, 2009.
Index sets and universal numberings. Sanjay, Jain, Frank Stephan and Jason Teutsch. In Journal of Computer and System Sciences, Volume 77, number 4, pages 760--773, 2011.
Regular Patterns, Regular Languages and Context-Free Languages. Sanjay Jain, Yuh Shin Ong and Frank Stephan. In Information Processing Letters, Volume 110, Issue 24, pages 1114--1119, 2010.
Iterative Learning of Simple External Contextual Languages. Leonor Becerra-Bonache, John Case, Sanjay Jain and Frank Stephan. In Theoretical Computer Science, Volume 411, Numbers 29--30, pages 2741--2756, 2010. Special Issue on Algorithmic Learning Theory, 2008.
Incremental Learning with Temporary Memory. Sanjay Jain, Steffen Lange, Samuel E. Moelius III and Sandra Zilles. In Theoretical Computer Science, Volume 411, Numbers 29-30, pages 2757--2772, 2010. Special Issue on Algorithmic Learning Theory, 2008.
Numberings Optimal for Learning. Sanjay Jain and Frank Stephan. In Journal of Computer and System Sciences, Volume 76, Pages 233--250, 2010.
Input-Dependence in Function-Learning. Sanjay Jain, Eric Martin and Frank Stephan. In Theory of Computing Systems, Volume 45, Issue 4, Pages 849--864, 2009. (Special Issue on Computability in Europe, 2007.)
On Some Open Problems in Monotonic and Conservative Learning. Sanjay Jain. In Information Processing Letters, pages 923--926, Volume 109, Number 16, July 2009.
One-shot Learners Using Negative Counterexamples and Nearest Positive Examples. Sanjay Jain and Efim Kinber. In Theoretical Computer Science, Volume 410, Numbers 27--29, pages 2562--2580, 2009.
Learning Correction Grammars. Lorenzo Carlucci, John Case and Sanjay Jain. In Journal of Symbolic Logic, Volume 74, Number 2, Pages 489--516, 2009.
Prescribed Learning of R.E. Classes. Sanjay Jain and Frank Stephan and Nan Ye. In Theoretical Computer Science, Volume 410, pages 1796--1806, 2009. (Special Issue on Algorithmic Learning Theory, 2007.)
On Some Open Problems in Reflective Inductive Inference. Sanjay Jain. In Information Processing Letters, pages 208--211, Volume 109, Number 3, January 2009.
Mitotic Classes in Inductive Inference. Sanjay Jain and Frank Stephan. In Siam Journal on Computing, Volume 38, Number 4, Pages 1283--1299, 2008.
Learning in Friedberg Numberings. Sanjay Jain and Frank Stephan. In Information and Computation, Volume 206, Number 6, pages 776--790, 2008.
Absolute versus Probabilistic Classification in a Logical Setting. Sanjay Jain, Eric Martin, and Frank Stephan. In Theoretical Computer Science, Volume 397, Number 1-3, pages 114--128, 2008. Special Issue on Forty Years of Inductive Inference. Dedicated to the 60th Birthday of Rolf Wiehagen.
Learning and Extending Sublanguages. Sanjay Jain and Efim Kinber. In Theoretical Computer Science, Volume 397, Number 1-3, pages 233--246, 2008. Special Issue on Forty Years of Inductive Inference. Dedicated to the 60th Birthday of Rolf Wiehagen.
Non-U-shaped Vacillatory and Team Learning. Lorenzo Carlucci and John Case and Sanjay Jain and Frank Stephan. In Journal of Computer and System Sciences, Volume 74, Number 4, 409--430, 2008.
Learning Languages from Positive Data and Negative Counterexamples. Sanjay Jain and Efim Kinber. In Journal of Computer and System Sciences, Volume 74, Number 4, 431--456, 2008.
Prescribed Learning of Indexed Families. Sanjay Jain and Frank Stephan and Nan Ye. In Fundamenta Informaticae, Volume 83, Number 1--2, 159--175, 2008.
Learning Languages from Positive Data and a Limited Number of Short Counterexamples. Sanjay Jain and Efim Kinber. In Theoretical Computer Science, Volume 389, Number 1--2, Pages 190--218, 2007.
Iterative Learning from Positive Data and Negative Counterexamples. Sanjay Jain and Efim Kinber. In Information and Computation, Volume 205, Number 12, 1777--1805, 2007.
Some Natural Conditions on Incremental Learning. Sanjay Jain, Steffen Lange and Sandra Zilles. In Information and Computation, Volume 205, Number 11, 1671--1684, 2007.
A General Comparision of Language Learning from Examples and from Queries. Sanjay Jain, Steffen Lange, and Sandra Zilles. In Theoretical Computer Science, Volume 387, Number 1, pages 51--66, 2007. (Special Issue on Algorithmic Learning Theory, 2005).
Learning Multiple Languages in Groups. Sanjay Jain and Efim Kinber. In Theoretical Computer Science, Volume 387, Number 1, pages 67--76. (Special Issue on Algorithmic Learning Theory, 2005).
Results on Memory-Limited U-Shaped Learning. Lorenzo Carlucci, John Case, Sanjay Jain and Frank Stephan. In Information and Computation, Volume 205, Number 10, pages 1551--1573, 2007.
Invertible Classes. Sanjay Jain, Jochen Nessel and Frank Stephan. In Theoretical Computer Science, Volume 384, Number 1, pages 49--65, 2007. (Special Issue on Theory and Models of Computation, 2006).
Learning Languages in a Union. Sanjay Jain, Yen Kaow Ng, and Tiong Seng Tay Journal of Computer and System Sciences, Volume 73, Number 1, pages 89--108, 2007.
Learning a Subclass of Regular Patterns in Polynomial Time. John Case, Sanjay Jain, R\"udiger Reischuk, Frank Stephan, Thomas Zeugmann. In Theoretical Computer Science, Volume 364, Issue 1, pages 115--131, 2006. Special Issue on Algorithmic Learning Theory (ALT 2003).
Variations on U-shaped learning. Lorenzo Carlucci, Sanjay Jain, Efim Kinber and Frank Stephan. Information and Computation, Volume 204, Number 8, pages 1264--1294, 2006.
Identifying Clusters from Positive Data. John Case, Sanjay Jain, Eric Martin, Arun Sharma and Frank Stephan. In SIAM Journal of Computing, Volume 36, Issues 1, pages 28--55, May 2006.
Generality's Price: Inescapable Deficiencies in Machine-Learned Programs. John Case, Keh-Jiann Chen, Sanjay Jain, Wolfgang Merkle and James S. Royer. Annals of Pure and Applied Logic, Volume 139, Issues 1--3, pages 303--326, May 2006.
Learning Languages from Positive Data and a Finite Number of Queries. Sanjay Jain and Efim Kinber. Information and Computation, Volume 204, Number 1, pages 123--175, 2006.
On Learning to Coordinate: Random Bits Help, Insightful Normal Forms and Competency Isomorphisms. John Case, Sanjay Jain, Franco Montagna, Giulia Simi and Andrea Sorbi. In Journal of Computer and System Sciences, pages 308--332, Volume 71, Number 3, 2005.
Robust Learning -- Rich and Poor. John Case, Sanjay Jain, Frank Stephan and Rolf Wiehagen. In Journal of Computer and System Sciences, pages 123--165, Volume 69, Number 2, 2004.
Learning All Subfunctions of a Function. Sanjay Jain, Efim Kinber and Rolf Wiehagen. In Information and Computation, pages 185--215, Volume 192, Number 2, August 2004.
Classes with Easily Learnable Subclasses. Sanjay Jain and Wolfram Menzel and Frank Stephan. In Information and Computation, pages 81--99, Volume 190, Number 1, April 2004.
Parsimony Hierarchies For Inductive Inference. Andris Ambainis, John Case, Sanjay Jain and Mandayam Suraj. In Journal of Symbolic Logic, pages 287--327, Volume 69, Number 1, March 2004.
Learning How to Separate. Sanjay Jain and Frank Stephan. In Theoretical Computer Science, pages 209--228, Volume 313, Number 2, February 2004. (Special Issue on Algorithmic Learning Theory, 2001).
Counting Extensional Differences in BC-Learning. Sanjay Jain, Frank Stephan and Sebastiaan A. Terwijn. In Information and Computation, pages 127--142, Volume 188, Number 1, January 2004.
Intrinsic Complexity of Learning Geometrical Concepts from Positive Data. Sanjay Jain and Efim Kinber. In Journal of Computer and System Sciences, pages 546--607, Volume 67, Number 3, 2003.
The Intrinsic Complexity of Learning: A Survey. Sanjay Jain. In Fundamenta Informaticae, pages 17--37, Volume 57, Number 1, October 2003.
Learning by Switching Type of Information. Sanjay Jain and Frank Stephan. In Information and Computation, pages 89--104, Volume 185, Number 1, 2003.
On the Intrinsic Complexity of Learning Recursive Functions. Sanjay Jain, Efim Kinber, Christophe Papazian, Carl Smith and Rolf Wiehagen. In Information and Computation, pages 45--70, Volume 184, Number 1, July 2003.
On Learning of Functions Refutably. Sanjay Jain, Efim Kinber, Rolf Wiehagen and Thomas Zeugmann. In Theoretical Computer Science, pages 111--143, Volume 298, Number 1, April 2003.
Mind Change Complexity of Learning Logic Programs. Sanjay Jain, and Arun Sharma. In Theoretical Computer Science, pages 143--160, Volume 284, Number 1, July 2002. Special issue on EuroCOLT' 99.
Control Structures in Hypothesis Spaces: The Influence on Learning. John Case, Sanjay Jain, and Mandayam Suraj. In Theoretical Computer Science, pages 287--308, Volume 270, Number 1--2, January 2002.
Language Learning from Texts: Degrees of Intrinsic Complexity and Their Characterizations. Sanjay Jain, Efim Kinber and Rolf Wiehagen. In Journal of Computer and System Sciences, pages 305--354, Volume 63, Number 3, November 2001.
Predictive Learning Models for Concept Drift. John Case, Sanjay Jain, Susanne Kaufmann, Arun Sharma and Frank Stephan. In Theoretical Computer Science, pages 323--349, Volume 268, Number 2, October 2001. Special issue on Algorithmic Learning Theory' 98.
Synthesizing Noise-Tolerant Language Learners. John Case, Sanjay Jain, and Arun Sharma. In Theoretical Computer Science, pages 31--56, Volume 261, Number 1, June 2001. Special issue on Algorithmic Learning Theory, 1997.
On the Learnability of Recursively Enumerable Languages from Good Examples. Sanjay Jain, Steffen Lange, and Jochen Nessel. In Theoretical Computer Science, pages 3--29, Volume 261, Number 1, June 2001. Special issue on Algorithmic Learning Theory, 1997.
Synthesizing Learners Tolerating Computable Noisy Data. John Case and Sanjay Jain. In Journal of Computer and System Sciences, pages 413--441, Volume 62, Number 3, May 2001.
Costs of General Purpose Learning. John Case, K. J. Chen, and Sanjay Jain. In Theoretical Computer Science, pages 455--473, Volume 259, Number 1--2, May, 2001.
On a Generalized Notion of Mistake Bounds. Sanjay Jain and Arun Sharma. In Information and Computation, pages 156--166, Volume 166, 2001.
On an Open Problem in Classification of Languages. Sanjay Jain. In Journal of Experimental and Theoretical Artificial Intelligence, pages 113--118, Volume 13, Number 2, April 2001.
Some Independence Results for Control Structures in Complete Numberings. Sanjay Jain and Jochen Nessel. In Journal of Symbolic Logic, pages 357--382, Volume 66, Number 1, March 2001.
Branch and Bound on the Network Model. Sanjay Jain. In Theoretical Computer Science, pages 107--123, Volume 255, Number 1--2, March, 2001.
Robust Learning is Rich. Sanjay Jain, Carl Smith, and Rolf Wiehagen. In Journal of Computer and System Sciences, pages 178--212, Volume 62, Number 1, 2001.
Learning Languages and Functions by Erasing. Sanjay Jain, Efim Kinber, Steffen Lange, Rolf Wiehagen, and Thomas Zeugmann. In Theoretical Computer Science, pages 143--189, Volume 241, Number 1--2, June, 2000. Special issue on Algorithmic Learning Theory, 1996.
Vacillatory and BC learning on noisy data. John Case, Sanjay Jain and Frank Stephan. In Theoretical Computer Science, pages 115--141, Volume 241, Number 1--2, June, 2000. Special issue on Algorithmic Learning Theory, 1996.
Robust Learning Aided by Context. John Case, Sanjay Jain, Matthias Ott, Arun Sharma and Frank Stephan. In Journal of Computer and System Sciences, pages 234--257, Volume 60, Number 2, April 2000. Special issue on COLT' 98.
Team Learning of Computable Languages. Sanjay Jain and Arun Sharma. In Theory of Computing Systems, pages 35--58, Volume 33, Number 1, 2000.
Robust Behaviourally Correct Learning. Sanjay Jain. In Information and Computation, pages 238--248, Volume 153, Number 2, September 1999.
The Synthesis of Language Learners. Ganesh Baliga, John Case and Sanjay Jain. In Information and Computation, pages 16--43, Volume 152, Number 1, July 1999.
Incremental Concept Learning for Bounded Data Mining. John Case, Sanjay Jain, Steffen Lange, and Thomas Zeugmann. In Information and Computation, pages 74--110, Volume 152, Number 1, July 1999.
Ordinal Mind Change Complexity of Language Identification. Andris Ambainis, Sanjay Jain, and Arun Sharma. In Theoretical Computer Science. pages 323-343, Volume 220, Number 2, June 1999. Special issue on Australasian Computer Science.
On a Question of Nearly Minimal Identification of Functions. Sanjay Jain. In Information Processing Letters, pages 113--117, Volume 70, Number 3, May 1999.
Learning with Refutation. Sanjay Jain. In Journal of Computer and System Sciences, pages 356--365, Volume 57, Number 3, December 1998.
Generalization and specialization strategies for learning r.e. languages. Sanjay Jain and Arun Sharma. In Annals of Mathematics and Artificial Intelligence, pages 1--26, Volume 23, 1998. Special Issue on Algorithmic Learning Theory and Analogical and Inductive Inference, 1994.
Minimal Concept Identification and Reliability. Sanjay Jain. In the International Journal of Foundations of Computer Science, pages 315--320, Volume 9--3, September 1998.
The Structure of Intrinsic Complexity of Learning. Sanjay Jain and Arun Sharma. In the Journal of Symbolic Logic, pages 1187-1201, Volume 62, Number 4, December 1997.
Kolmogorov Numberings and Minimal Identification. Rusins Freivalds and Sanjay Jain. In Theoretical Computer Science, pages 175--194, Volume 188, Number 1--2, November 1997.
Learning from Multiple Sources of Inaccurate Data. Ganesh Baliga, Sanjay Jain and Arun Sharma. In Siam Journal on Computing, pages 961--990, Volume 26, Number 4, August 1997.
Characterizing Language Identification in Terms of Computable Numbering. Sanjay Jain and Arun Sharma. In Annals of Pure and Applied Logic, pages 51--72, Volume 84, Number 1, March 6, 1997. Special issue on Asian Logic Conference, 1993.
Strong Monotonic and Set Driven Inductive Inference. Sanjay Jain. In the Journal of Experimental and Theoretical Artificial Intelligence, pages 137--143, Volume 9, Number 1, March 1997.
Elementary Formal Systems, Intrinsic Complexity and Procrastination. Sanjay Jain and Arun Sharma. In Information and Computation, pages 65--84, Volume 132, Number 1, January 10, 1997.
Program Synthesis in the Presence of Infinite Number of Inaccuracies. Sanjay Jain. In Journal of Computer and System Sciences, pages 583--591, Volume 53, Number 3, December 1996.
Computational Limits on Team Identification of Languages. Sanjay Jain and Arun Sharma. In Information and Computation, pages 19--60, Volume 130, Number 1, October 10, 1996.
Anomalous Learning Helps Succinctness. John Case, Sanjay Jain and Arun Sharma. In Theoretical Computer Science, pages 13--28, Volume 164, Numbers 1--2, 10 September 1996.
Machine Induction Without Revolutionary Changes in Hypothesis Size. John Case, Sanjay Jain and Arun Sharma. In Information and Computation, pages 73--86, Volume 128, Number 2, August 1, 1996.
Learning in the Presence of Inaccurate Information. Mark Fulk and Sanjay Jain. In Theoretical Computer Science, pages 235--261, Volume 161, Numbers 1--2, 15 July 1996.
The Intrinsic Complexity of Language Identification. Sanjay Jain and Arun Sharma. In the Journal of Computer and System Sciences, pages 393--402, Volume 52--3, June 1996. Special issue on Computational Learning Theory, 1994.
Language Learning with Some Negative Information. Ganesh Baliga, John Case and Sanjay Jain. Journal of Computer and System Sciences, pages 273--285, Volume 51--2, October 1995.
Finite Identification of Functions by Teams with Success Ratio 1/2 and Above. Sanjay Jain, Arun Sharma and Mahendran Velauthapillai. Information and Computation, pages 201--213, Volume 121--2, September 1995.
Prudence in Vacillatory Language Identification. Sanjay Jain and Arun Sharma. Mathematical Systems Theory, pages 267--279, Volume 28--3, May-June 1995.
An Infinite Class of Functions Identifiable Using Minimal Programs in all Kolmogorov Numberings. Sanjay Jain. International Journal of Foundations of Computer Science, pages 89--94, Volume 6--1, March 1995.
Complexity Issues for Vacillatory Function Identification. John Case, Sanjay Jain and Arun Sharma. Information and Computation, pages 174--192, Volume 116--2, February 1, 1995.
On a Question about Learning Nearly Minimal Programs. Sanjay Jain. Information Processing Letters, pages 1--4, Volume 53--1, January 13, 1995.
On Aggregating Teams of Learning Machines. Sanjay Jain and Arun Sharma. Theoretical Computer Science, pages 85--108, Volume 137--1, January 9, 1995. Special issue on Algorithmic Learning Theory, 1993.
Open Problems in Systems that Learn. Mark Fulk, Sanjay Jain and Daniel Osherson. Journal of Computer and System Sciences, pages 589--604, Volume 49--3, December 1994.
Approximate Inference and Scientific Method. Mark Fulk and Sanjay Jain. Information and Computation, pages 179--191, Volume 114--2, November 1, 1994.
Vacillatory Learning of Nearly Minimal Size Grammars. John Case, Sanjay Jain and Arun Sharma. Journal of Computer and System Sciences, pages 189--207, Volume 49--2, October 1994.
Characterizing Language Identification by Standardizing Operations. Sanjay Jain and Arun Sharma. Journal of Computer and System Sciences, pages 96--107, Volume 49--1, August 1994.
Machine Learning of Higher Order Programs. Ganesh Baliga, John Case, Sanjay Jain and Mandayam Suraj. Journal of Symbolic Logic, pages 486--500, Volume 59--2, June 1994.
Program Size Restrictions in Computational Learning. Sanjay Jain and Arun Sharma. Theoretical Computer Science, pages 351--386, Volume 127--2, 23 May 1994.
Extremes in the Degrees of Inferability. L. Fortnow, W. Gasarch, S. Jain, E. Kinber, M. Kummer, S. Kurtz, M. Pleszkoch, T. Slaman, R. Solovay, F. Stephan. Annals of Pure and Applied Logic, pages 231--276, Volume 66--3, 5 April 1994.
Refinements of Inductive Inference by Popperian and Reliable Machines. John Case, Sanjay Jain and Suzanne Ngo Manguelle. Kybernetika, pages 23--52, Volume 30--1, 1994.
Banishing Robust Turing Completeness. Lane Hemaspaandra, Sanjay Jain and Nikolai Vereshchagin. International Journal of Foundations of Computer Science, pages 245--265, Volume 4--3, September 1993.
On the non-existence of maximal inference degrees for language identification. Sanjay Jain and Arun Sharma. Information Processing Letters, pages 81--88, Volume 47--2, 20 August 1993.
Learning with the Knowledge of an Upper Bound on Program Size. Sanjay Jain and Arun Sharma. Information and Computation, pages 118--166, Volume 102--1, January 1993.
Strong Separation of Learning Classes. John Case and Keh-Jiann Chen and Sanjay Jain. Journal of Experimental and Theoretical Artificial Intelligence, pages 281--293, Volume 4--4, October--December 1992.
On Learning Limiting Programs. John Case, Sanjay Jain and Arun Sharma. International Journal of Foundations of Computer Science, pages 93--115, Volume 3--1, March 1992.
Learning in the Presence of Partial Explanations. Sanjay Jain and Arun Sharma, Information and Computation, pages 162--191, Volume 95--2, December 1991.
On the Limitations of Locally Robust Positive Reductions. Lane Hemachandra and Sanjay Jain. International Journal of Foundations of Computer Science, pages 237--255, Volume 2--3, September 1991.
Computational Complexity of Learning. Sanjay Jain and Frank Stephan. In Encyclopedia of Machine Learning, Edited by Claude Sammut and Geoff Web, Springer, Berlin, pages 201--202, 2010.
Query-Based Learning. Sanjay Jain and Frank Stephan. In Encyclopedia of Machine Learning, Edited by Claude Sammut and Geoff Web, Springer, Berlin, pages 820--822, 2010.
Complexity of Inductive Inference. Sanjay Jain and Frank Stephan. In Encyclopedia of Machine Learning, Edited by Claude Sammut and Geoff Web, Springer, Berlin, pages 198--201, 2010.
Inductive Inference. Sanjay Jain and Frank Stephan. In Encyclopedia of Machine Learning, Edited by Claude Sammut and Geoff Web, Springer, Berlin, pages 523--528, 2010.
Connections between Inductive Inference and Machine Learning. John Case and Sanjay Jain. In Encyclopedia of Machine Learning, Edited by Claude Sammut and Geoff Web, Springer, Berlin, pages 210--219, 2010.
A Tour of Robust Learning. Sanjay Jain and Frank Stephan. In B. Cooper and S. Goncharov, editors, Computability and Models, Perspectives East and West, pages 215--247. Kluwer Academic/Plenum Publishers, University Series in Mathematics, 2003.
Not-So-Nearly-Minimal-Size Inductive Inference. John Case and Mandayam Suraj and Sanjay Jain. In Klaus P. Jantke and Steffen Lange, editors, Algorithmic Learning for Knowledge-Based Systems, pages 76--95. Lecture Notes in Artificial Intelligence 961. Springer Verlag, 1995.
On Identification by Teams and Probabilistic Machines. Sanjay Jain and Arun Sharma. In Klaus P. Jantke and Steffen Lange, editors, Algorithmic Learning for Knowledge-Based Systems, pages 108--145. Lecture Notes in Artificial Intelligence 961. Springer Verlag, 1995.
Learnability and Positive Equivalence Relations. David Belanger, Ziyuan Gao, Sanjay Jain, Wei Li and Frank Stephan. Language and Automata Theory and Applications, 15th International Conference, LATA 2021. In Alberto Leporati, Carlos Martin-Vie, Dana Shapira, Claudio Zandron, editors, Language and Automata Theory and Applications, 15th International Conference, LATA 2021, pages 145--156. Lecture Notes in Computer Science 12638. Springer Verlag, 2021.
A faster exact algorithm to count X3SAT solutions. Gordon Hoi, Sanjay Jain and Frank Stephan. In Helmut Simonis (Ed.), Principles and Practice of Constraint Programming, 26th International Conference, CP2020, pages 375--391. Lecture Notes in Computer Science 12333. Springer Verlag, 2020.
Ordered Semiautomatic Rings with Applications to Geometry. Ziyuan Gao, Sanjay Jain, Ji Qi, Philipp Schlicht, Frank Stephan and Jacob Tarr. In Alberto Leporati, Carlos Martin-Vie, Dana Shapira, Claudio, editors, Language and Automata Theory and Applications, LATA 2020.
A Fast Exponential Time Algorithm for Max Hamming Distance X3SAT. Gordon Hoi, Sanjay Jain and Frank Stephan. In Arkadev Chattopadhyay and Paul Gastin, editors, 39th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science, FSTTCS 2019. ISBN 978-3-95977-131-3, LIPICS Vol. 150, pages 17:1--17:14, 2019.
Near Polynomial Time Algorithms for Parity Games. Sanjay Jain. Invited talk at 21st International Workshop on Verification of Infinite State Systems, Infinity 2019.
Random Subgroups of Rationals. Ziyuan Gao, Sanjay Jain, Bkhadyr Khoussainov, Wei Li, Alexander Melnikov, Karen Seidel and Frank Stephan. In Peter Rossmanith, Pinar Heggernes and Joost-Pieter Katoen, editors, 44th International Symposium on Mathematical Foundations of Computer Science (MFCS 2019), 2019. Leibniz International Proceedings in Informatics (LIPIcs), Volume 138, pages 25:1--25:14, 2019.
Exact Satisfiability with Jokers. Gordon Hoi, Sanjay Jain, Sibylle Schwarz and Frank Stephan. In T. V. Gopal and J. Watada, editors, TAMC 2019, Theory and Applications of Models of Computation, pages 279--294. Lecture Notes in Computer Science 11436. Springer Verlag, 2019.
Survey of Some Recent near Polynomial Times Results for Parity Games. Sanjay Jain. Invited talk. In Costas Iliopoulos, Hon Wai Leong and Wing-Kin Sung, editors, Combinatorial Algorithms, 29th International Workshop, IWOCA 2018, Singapore. Lecture Notes in Computer Science, 10979, Springer Verlag 2018.
On the Help of Bounded Shot Verifiers, Comparators, and Standardisers for Learnability in Inductive Inference. Ziyuan Gao, Sanjay Jain, Frank Stephan and Thomas Zeugmann. In, Firdaus Janoos, Mehryar Mohri and Karthik Sridharan, editors, Algorithmic Learning Theory, 29th International Conference, ALT' 19, pages 413--437, 2018. Volume 83 of the JMLR Workshop and Conference Proceedings Series, 2018.
Learners Based on Transducers. Sanjay Jain, Shao Ning Kuek, Eric Martin and Frank Stephan. In, Shmuel Tomi Klein, Carlos Martin-Vide and Dana Shapira, editors, Language and Automata Theory and Applications, 12th International Conference, LATA 2018, pages 169--181. Lecture Notes in Computer Science 10792. Springer Verlag, 2018.
Quasipolynomial and FPT Algorithms for Parity Games. Cristian S. Calude, Sanjay Jain, Bakhadyr Khoussainov, Wei Li and Frank Stephan. Invited Talk at Highlights of Logic, Games and Automata, London, 12--15 September, 2017. Also, Invited Talk at IMS Workshop on Parametric Complexity, Aspects of Computation, Singapore, 21--25 August, 2017.
Automatic Learning from Repetitive Texts. Rupert Holzl, Sanjay Jain, Philipp Schlicht, Karen Seidel and Frank Stephan. In Algorithmic Learning Theory, 28th International Conference, ALT' 17, pages 129--150, 2017. Volume 76 of the JMLR Workshop and Conference Proceedings Series, 2017.
An Ordered Approach to Solving Parity Games in Quasi Polynomial Time and Quasi Linear Space. John Fearnly, Sanjay Jain, Sven Schewe, Frank Stephan and Dominik Wojtczak. In SPIN 2017, The Proceedings of the 24th International ACM SIGSOFT International SPIN Symposium on Model Checking of Software, pages 112--121, 2017.
Deciding Parity Games in Quasipolynomial Time. Cristian S. Calude, Sanjay Jain, Bakhadyr Khossainov, Wei Li and Frank Stephan. In the 49th Annual ACM Symposium on the Theory of Computing, pages 252--263, 2017. (Best paper award)
Learning Pattern Languages Over Groups. Rupert Holzl, Sanjay Jain and Frank Stephan. Sanjay Jain and Efim Kinber. In Ronald Ortner, Hans Ulrich Simon and Sandra Zilles, editors, Algorithmic Learning Theory, 27th International Conference, ALT' 16, 2016. pages 189--203. Lecture Notes in Artificial Intelligence 9925. Springer Verlag, 2016.
Intrinsic Complexity of Partial Learning. Sanjay Jain and Efim Kinber. In Ronald Ortner, Hans Ulrich Simon and Sandra Zilles, editors, Algorithmic Learning Theory, 27th International Conference, ALT' 16, 2016. pages 174--188. Lecture Notes in Artificial Intelligence 9925. Springer Verlag, 2016.
Finitely Generated Semiautomatic Groups. Sanjay Jain, Bakhadyr Khoussainov and Frank Stephan. In Arnold Beckmann, Laurent Bienvenu and Natasa Jonoska, editors, Pursuit of the Universal, 12th conference on Computability in Europe (CiE) 2016, pages 282--291. Lecture Notes in Computer Science, Volume 9709, 2016.
Learning automatic families of languages. Sanjay Jain and Frank Stephan. In, Rusins Martins Freivalds, Gregor Engels and Barbara Catania, editors. SOFSEM 2016, Theory and Practice of Computer Science, 42nd International Conference on Current Trends in Theory and Practice of Computer Science, 2016, pages 29--40. Lecture notes in Computer Science 9587. Springer Verlag, 2016.
When cryptocurrencies mine their own business. Jason Teutsch, Sanjay Jain and Prateek Saxena. In, Jens Grossklags and Bart Preneel, editors, Financial Cryptography and Data Security - 20th International Conference, FC 201 6.
Priced Learning. Sanjay Jain, Ma Junqi and Frank Stephan. In Kamalika Chaudhuri, Claudio Gentile and Sandra Zilles, editors, Algorithmic Learning Theory, 26th International Conference, ALT' 15, 2015. pages 41--55. Lecture Notes in Artificial Intelligence 9355. Springer Verlag, 2015.
Enumerations including laconic enumerators. Sanjay Jain and Jason Teutsch. In Tenth International Conference on Computability, Complexity and Randomness (CCR) 2015.
Complexity of Semiautomatic Structures. Sanjay Jain, Bkahadyr Khoussainov, Frank Stephan, Dan Teng and Siyuan Zou. In Tenth International Conference on Computability, Complexity and Randomness (CCR) 2015.
Inductive Inference and Reverse Mathematics. Rupert Holzl, Sanjay Jain and Frank Stephan. In Ernst W. Mayr and Nocolas Ollinger, 32nd International Symposium on Theoretical Aspects of Computer Science (STACS 2015), pages 420--433. Leibniz International Proceedings in Informatics (LIPIcs), Vol 30, 2015. Expanded Version of the paper.
A Survey on Recent Results on Partial Learning. Ziyuan Gao, Sanjay Jain, Frank Stephan and Sandra Zilles Proceedings of the Thirteenth Asian Logic Conference, World Scientific, pages 68--92, 2015.
Parallel Learning of Automatic Classes of Languages. Sanjay Jain and Efim Kinber. In Peter Auer, Alexander Clark, Thomas Zeugmann and Sandra Zilles, editors, Algorithmic Learning Theory, 25th International Conference, ALT' 14, 2014, pages 70--84. Lecture Notes in Artificial Intelligence 8776. Springer Verlag, 2014. Expanded Version of the paper.
On the Role of Update Constraints and Text-Types in Iterative Learning. Sanjay Jain, Timo Koetzing, Junqi Ma, and Frank Stephan. In Peter Auer, Alexander Clark, Thomas Zeugmann and Sandra Zilles, editors, Algorithmic Learning Theory, 25th International Conference, ALT' 14, 2014, pages 55--69. Lecture Notes in Artificial Intelligence 8776. Springer Verlag, 2014. Expanded Version of the paper.
Semiautomatic Structures. Sanjay Jain, Bakshadyr Khoussainov, Frank Stephan, Dan Teng and Siyuan Zou. In E. A. Hirsch, S. O. Kuznetsov, J. E. Pin, N. K. Vereshchagin, editors, Computer Science --- Theory and Applications, 9th International Computer Science Symposium in Russia (CSR 2014), pages 204--217, Moscow, Russia 2014. Lecture Notes in Computer Science, Volume 8476, 2014. Expanded Version of the paper.
Closed Left-R.E. Sets -- Recent Progress. Sanjay Jain, Frank Stephan and Jason Teutsch. Eighth International Conference on Computability, Complexity and Randomness (CCR 2013), Moscow, Russia 2013.
Graphs realised by r.e. equivalence relations. Alexander Gavruskin, Sanjay Jain, Bakhadyr Khoussainov and Frank Stephan. presented at Computability in Europe: The Nature of Computation, (CiE) 2013. Expanded Version of the paper.
On Conservative Learning of Recursively Enumerable Languages. Ziyuan Gao, Sanjay Jain and Frank Stephan. In, P. Bonizzoni, V. Brattka, B. Lowe, editors, 9th Conference on Computability in Europe: The Nature of Computation, Logic, Algorithms, Applications, (CiE) 2013, Milan, Italy, pages 181--190. Lecture Notes in Computer Science, Volume 7921, 2013. Expanded Version of the paper.
Effectivity questions for Kleene's recursion theorem. John Case, Sanjay Jain and Frank Stephan. In S. Artemov and A. Nerode, editors, Symposium on Logical Foundations in Computer Science (LFCS), 2013. Lecture Notes in Computer Science, Volume 7734, Springer, pages 89--103, 2013. Expanded Version of the paper.
Automatic Learning from Positive Data and Negative Counterexamples. Sanjay Jain and Efim Kinber. In Nader Bshouty, Gilles Stoltz, Nicolas Vayatis and Thomas Zeugmann, editors, Algorithmic Learning Theory, 23nd International Conference, ALT' 12, 2012, pages 66--80. Lecture Notes in Artificial Intelligence 7568. Springer Verlag, 2012.
Enlarging Learnable Classes. Sanjay Jain, Timo Kotzing and Frank Stephan. In Nader Bshouty, Gilles Stoltz, Nicolas Vayatis and Thomas Zeugmann, editors, Algorithmic Learning Theory, 23nd International Conference, ALT' 12, 2012, pages 36--50. Lecture Notes in Artificial Intelligence 7568. Springer Verlag, 2012.
The Complexity of Verbal Languages over Groups Sanjay Jain, Alexei Miasnikov and Frank Stephan. In 27th Annual ACM/IEEE Symposium on Logic in Computer Science, (LICS) 2012, pages 405--414. IEEE Computer Society, 2012.
Automatic Functions, Linear Time and Learning. John Case, Sanjay Jain and Frank Stephan. In, S. B. Cooper, A. Sawar and B. L{\"o}we, editors, Computability in Europe: How the world computes -- Turing Centenary Coference and Eighth Conference on Computability in Europe, (CiE) 2012, pages 96--106. Lecture Notes in Computer Science 7318. Springer Verlag, 2012.
On the Amount of Nonconstructivity in Learning Formal Languages from Positive Data. Sanjay Jain, Frank Stephan and Thomas Zeugmann. In Manindra Agrawal, S. Barry Cooper and Angsheng Li, editors, Theory and Applications of Models of Computation, 9th Annual Conference, (TAMC) 2012, pages 423--434. Lecture Notes in Computer Science 7287. Springer Verlag, 2012.
Mind change speed-up for learning languages from positive data. Sanjay Jain and Efim Kinber. In, C. Durr and T. Wilke, 29th International Symposium on Theoretical Aspects of Computer Science (STACS 2012), 2012, pages 350--361. Leibniz International Proceedings in Informatics (LIPIcs), Volume 14. Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik, 2012. Expanded Version of the paper.
Robust learning of automatic classes of languages. Sanjay Jain, Eric Martin and Frank Stephan. In J. Kivinen, C. Szepesvari, E. Ukkonen and T. Zeugmann, Algorithmic Learning Theory, 22nd International Conference, ALT' 11, 2011, pages 55--69. Lecture Notes in Artificial Intelligence 6925. Springer Verlag, 2011. Expanded Version of the paper.
Learning and Classifying. Sanjay Jain, Eric Martin and Frank Stephan. In J. Kivinen, C. Szepesvari, E. Ukkonen and T. Zeugmann, Algorithmic Learning Theory, 22nd International Conference, ALT' 11, 2011, pages 70--83. Lecture Notes in Artificial Intelligence 6925. Springer Verlag, 2011. Expanded Version of the paper.
On Automatic Families. Sanjay Jain, Yuh Shin Ong, Shi Pu, Frank Stephan. In T. Arai, Q. Feng, B. Kim, G. Wu and Y. Yang, Proceedings of the 11th Asian Logic Conference, in Honor of Professor Chong Chitat's 60th birthday, 2009. Pages 94--113. World Scientific, 2011.
Closed Left-r.e. sets. Sanjay Jain, Frank Stephan and Jason Teutsch. In, Mitsunori Ogihara and Jun Tarui, editors, Theory and Applications of Models of Computation, 8th Annual Conference (TAMC), 2011, pages 218--229. Lecture Notes in Computer Science 6648. Springer Verlag, 2011.
Automatic Learners with Feedback Queries. John Case, Sanjay Jain, Yuh Shin Ong, Pavel Semukhin and Frank Stephan. In, B. L{\"o}we, D. Norman, I. Soskov and A. Soskova, editors, Models of Computation in Context, Seventh Conference on Computability in Europe (CiE), 2011, pages 31--40. Lecture Notes in Computer Science 6735. Springer Verlag, 2011. Expanded Version of the paper.
Automatic Learning of Subclasses of Pattern Languages. John Case, Sanjay Jain, Trong Dao Le, Yuh Shin Ong, Pavel Semukhin and Frank Stephan. In, A. H. Dediu, S. Inenaga and C. Martin-Vide (editors), Language and Automata Theory and Applications, 5th international Confernece, LATA, 2011, pages 192--203. Lecture Notes in Computer Science 6638. Springer Verlag, 2011. Expanded Version of the paper.
Inductive Inference of Languages from Samplings. Sanjay Jain and Efim Kinber. In, Marcus Hutter, Frank Stephan, Vladimir Vovk and Thomas Zeugmann, editors, Algorithmic Learning Theory, 21st International Conference, ALT' 10, Canberra, Australia, October 2010, pages 330--344. Lecture Notes in Artificial Intelligence 6331. Springer Verlag, 2010.
Learnability of Automatic Classes. Sanjay Jain, Qinglong Luo and Frank Stephan. In A. H. Dediu, H. Fernau and C. Martin-Vide, editors, 4th International Conference on Language and Automata Theory and Applications (LATA 2010). Trier, Germany, May 24--28, 2010, pages 321--332. Lecture Notes in Computer Science 6031. Springer Verlag, 2010. Expanded Version of the paper.
Iterative Learning from Texts and Counterexamples Using Additional Information. Sanjay Jain and Efim Kinber. In Algorithmic Learning Theory, 20th International Conference, ALT' 09, Porto, Portugal, October 2009, pages 308--322. Lecture Notes in Artificial Intelligence 5809. Springer Verlag, 2009. Expanded Version of the paper.
Uncountable Automatic CLasses and Learning. Sanjay Jain, Qinglong Luo, Pavel Semukhin and Frank Stephan. In Algorithmic Learning Theory, 20th International Conference, ALT' 09, Porto, Portugal, October 2009, pages 293--307. Lecture Notes in Artificial Intelligence 5809. Springer Verlag, 2009. Expanded Version of the paper.
Learning From Streams. Sanjay Jain, Frank Stephan and Nan Ye. In Algorithmic Learning Theory, 20th International Conference, ALT' 09, Porto, Portugal, October 2009, pages 338--352. Lecture Notes in Artificial Intelligence 5809. Springer Verlag, 2009.
Consistent Partial Learning. Sanjay Jain and Frank Stephan. In, Adam Klivans and Sanjoy Dasgupta, editors, Conference on Learning Theory, Montreal, Canada, 2009.
Hypothesis Spaces for Learning. Sanjay Jain. In A. H. Dediu, A. M. Ionescu and C. Martin-Vide, editors, 3rd International Conference on Language and Automata Theory and Applications (LATA 2009), Tarragona, Spain, April 2-8, 2009, pages 43--58. Lecture Notes in Artificial Intelligence 5254. Springer Verlag, 2009. Expanded Version of the paper.
Numberings Optimal for Learning. Sanjay Jain and Frank Stephan. In Yoav Freund, Laszlo Gyorfi, Gyorgy Turan and Thomas Zeugmann, Algorithmic Learning Theory, 19th International Conference, ALT' 08, Budapest, Hungary, October 2008, pages 434--448. Lecture Notes in Artificial Intelligence 5254. Springer Verlag, 2008. Expanded Version of the paper.
Iterative Learning of Simple External Contextual Languages. Leonor Becerra-Bonache, John Case, Sanjay Jain and Frank Stephan. In Yoav Freund, Laszlo Gyorfi, Gyorgy Turan and Thomas Zeugmann, Algorithmic Learning Theory, 19th International Conference, ALT' 08, Budapest, Hungary, October 2008, pages 359--373. Lecture Notes in Artificial Intelligence 5254. Springer Verlag, 2008. Expanded Version of the paper.
Prescribed Learning of Indexed Families. Sanjay Jain and Frank Stephan and Nan Ye. In Arnold Beckmann, Costas Dimitracopoulos, Benedikt Lowe, editors Logic and Theory of Algorithms, Fouth Conference on Computability in Europe (CiE), Athens, Greece, pages 185--194, June 2008. Expanded Version of the paper.
One-shot Learners Using Negative Counterexamples and Nearest Positive Examples. Sanjay Jain and Efim Kinber. In M. Hutter, R. Servedio and E. Takimoto, editors, Algorithmic Learning Theory, 18th International Conference, ALT' 07, Sendai, Japan, October 2007, pages 257--271. Lecture Notes in Artificial Intelligence 4754. Springer Verlag, 2007. Expanded Version of the paper.
Learning in Friedberg Numberings. Sanjay Jain and Frank Stephan. In M. Hutter, R. Servedio and E. Takimoto, editors, Algorithmic Learning Theory, 18th International Conference, ALT' 07, Sendai, Japan, October 2007, pages 79--93. Lecture Notes in Artificial Intelligence 4754. Springer Verlag, 2007. Expanded Version of the paper.
Prescribed Learning of R.E. Classes. Sanjay Jain, Frank Stephan and Nan Ye. In M. Hutter, R. Servedio and E. Takimoto, editors, Algorithmic Learning Theory, 18th International Conference, ALT' 07, Sendai, Japan, October 2007, pages 64--78. Lecture Notes in Artificial Intelligence. Springer Verlag, 2007. Expanded Version of the paper.
Input-Dependence in Function-Learning. Sanjay Jain, Eric Martin and Frank Stephan. In S. B. Cooper, B. Lowe and A. Sorbi, editors, Computation and Logic in the Real World, Third Conference on Computability in Europe, CiE, Proceedings, Siena, Italy, 2007, pages 378--388. Lecture Notes in Computer Science 4497. Springer Verlag, 2007. Expanded version of the paper.
Learning Correction Grammars. Lorenzo Carlucci, John Case and Sanjay Jain. In, Nader Bshouty and Claudio Gentile, editors, Proceedings of the 20th Annual Conference on Learning Theory, 2007, pages 203--217. Lecture Notes in Artificial Intelligence 4539, Springer Verlag, 2007. Expanded Version of the paper.
mitotic Classes. Sanjay Jain and Frank Stephan. In, Nader Bshouty and Claudio Gentile, editors, Proceedings of the 20th Annual Conference on Learning Theory, 2007, pages 218--232. Lecture Notes in Artificial Intelligence 4539, Springer Verlag, 2007. Expanded Version of the paper.
Towards a Better Understanding of Iterative Learning. Sanjay Jain, Steffen Lange and Sandra Zilles. In J. L. Balcazar, P. Long and F. Stephan, editors, Algorithmic Learning Theory, 17th International Conference, ALT' 06, Barcelona, October 2006, pages 169--183. Lecture Notes in Artificial Intelligence 4264. Springer Verlag, 2006. Expanded Version of the paper.
Iterative Learning from Positive Data and Negative Counterexamples. Sanjay Jain and Efim Kinber. In J. L. Balcazar, P. Long and F. Stephan, editors, Algorithmic Learning Theory, 17th International Conference, ALT' 06, Barcelona, October 2006, pages 154--168. Lecture Notes in Artificial Intelligence 4264. Springer Verlag, 2006. Expanded version of the paper.
Learning and Extending Sublanguages. Sanjay Jain and Efim Kinber. In J. L. Balcazar, P. Long and F. Stephan, editors, Algorithmic Learning Theory, 17th International Conference, ALT' 06, Barcelona, October 2006, pages 139--153. Lecture Notes in Artificial Intelligence 4264. Springer Verlag, 2006. Expanded version of the paper.
Memory-Limited U-Shaped Learning. Lorenzo Carlucci, John Case, Sanjay Jain and Frank Stephan. In, Gabor Lugosi and Hans Ulrich Simon, editors, Proceedings of the 19th Annual Conference on Learning Theory, pages 244--258. Lecture Notes in Artificial Intelligence 4005, Spring Verlag, 2006. Expanded version of the paper.
On Learning Languages from Positive Data and a Limited Number of Short Counterexamples. Sanjay Jain and Efim Kinber. In, Gabor Lugosi and Hans Ulrich Simon, editors, Proceedings of the 19th Annual Conference on Learning Theory, pages 259--273. Lecture Notes in Artificial Intelligence 4005. Spring Verlag, 2006. Expanded version of the paper.
Invertible Classes. Sanjay Jain, Jochen Nessel, and Frank Stephan. In Jin-Yi Cai, S. Barry Cooper and Angsheng Li, editors, TAMC 2006, Theory and Applications of Models of Computation, Beijing, China, 2006, pages 707--720. Lecture Notes in Computer Science 3959. Spring Verlag, 2006. Expanded version of the paper.
Some Recent Results in U-Shaped Learning. Sanjay Jain and Frank Stephan. In Jin-Yi Cai, S. Barry Cooper and Angsheng Li, editors, TAMC 2006, Theory and Applications of Models of Computation, Beijing, China, 2006, pages 421--431. Lecture Notes in Computer Science 3959. Spring Verlag, 2006.
Absolute versus Probabilistic Classification in a Logical Setting. Sanjay Jain, Eric Martin, and Frank Stephan. In S. Jain, H. U. Simon and E. Tomita, editors, Algorithmic Learning Theory, 16th International Conference, ALT' 05, Singapore, October 2005, pages 327--342. Lecture Notes in Artificial Intelligence 3734. Springer Verlag, 2005. Expanded version of the paper.
Non U-Shaped Vacillatory and Team Learning. Lorenzo Carlucci, John Case, Sanjay Jain, and Frank Stephan. In S. Jain, H. U. Simon and E. Tomita, editors, Algorithmic Learning Theory, 16th International Conference, ALT' 05, Singapore, October 2005, pages 241--255. Lecture Notes in Artificial Intelligence 3734. Springer Verlag, 2005. Expanded version of the paper.
Gold-style and Query Learning under Various Constraints on the Target Class. Sanjay Jain, Steffen Lange, and Sandra Zilles. In S. Jain, H. U. Simon and E. Tomita, editors, Algorithmic Learning Theory, 16th International Conference, ALT' 05, Singapore, October 2005, pages 226--240. Lecture Notes in Artificial Intelligence 3734. Springer Verlag, 2005. Expanded version of the paper.
Learning Multiple Languages in Groups. Sanjay Jain and Efim Kinber. In S. Jain, H. U. Simon and E. Tomita, editors, Algorithmic Learning Theory, 16th International Conference, ALT' 05, Singapore, October 2005, pages 256--268. Lecture Notes in Artificial Intelligence 3734. Springer Verlag, 2005. Expanded version of the paper.
Negative Data in Learning Languages. Sanjay Jain and Efim Kinber. (Invited Talk) In The 9th Asian Logic Conference, pages 11--15. Novosibirsk, Russia 2005. Expanded version of the paper.
Variations on U-shaped learning. Lorenzo Carlucci, Sanjay Jain, Efim Kinber and Frank Stephan. In, P. Auer and R. Meir, editors, Proceedings, 18th Annual Conference on Learning Theory (COLT), Bertinoro, Italy, pages 382--397. Lecture Notes in Artificial Intelligence 3559. Springer Verlag 2005. Expanded version of the paper.
Learning Languages from Positive Data and a Finite Number of Queries. Sanjay Jain and Efim Kinber. In Kamal Lodaya and Meena Mahajan, editors, Proceedings of Foundations of Software Technology and Theoretical Computer Science, Chennai, India, December, 2004, pages 360--371. Lecture Notes in Artificial Intelligence 3328. Springer Verlag, 2004. Expanded version of the paper.
Identifying Clusters from Positive Data. John Case, Sanjay Jain, Eric Martin, Arun Sharma and Frank Stephan. In G. Paliouras and Y. Sakakibara, editors, Proceedings of the 7th International Colloquium on Grammatical Inference (ICGI'04), Athens, Greece, October 2004, pages 103-114. Lecture Notes in Artificial Intelligence 3264. Springer Verlag, 2004. Expanded version of the paper.
Learning Languages from Positive Data and Negative Counterexamples. Sanjay Jain and Efim Kinber. In Shai Ben-David, John Case, Akira Maruoka, editors, Algorithmic Learning Theory, 15th International Conference, ALT' 04, Padova, Italy, October 2004, pages 54--68. Lecture Notes in Artificial Intelligence 3244. Springer Verlag, 2004. Expanded version of the paper.
U-Shaped Learning May Be Necessary. Lorenzo Carlucci, John Case, Sanjay Jain and Frank Stephan. 37th Annual Meeting of the Society for Mathematical Psychology, Ann Arbor, Michigan, USA. July-August, 2004. Abstract in Journal of Mathematical Psychology, p97, volume 49, number 1, February 2005. Expanded version of the paper.
Learning a Subclass of Regular Patterns in Polynomial Time. John Case, Sanjay Jain, R\"udiger Reischuk, Frank Stephan and Thomas Zeugmann. In Algorithmic Learning Theory, 14th International Conference, ALT' 03, Soporo, Japan, October 2003. Lecture Notes in Artificial Intelligence. Springer Verlag, 2003. Expanded version of the paper.
Generality's Price: Inescapable Deficiencies in Machine-Learned Programs. John Case, K-J. Chen, Sanjay Jain, Wolfgang Merkle and James S. Royer. In, Bernhard Sch\"olkopf and Manfred Warmuth, editors, Proceedings, 16th Annual Conference on Learning Theory (COLT) and 7th Annual Workshop on Kernel Machines, Proceedings, Washington D. C., pages 684--698. Lecture Notes in Artificial Intelligence 2777. Springer Verlag 2003. Expanded version of the paper.
On Learning to Coordinate: Random Bits Help, Insightful Normal Forms and Competency Isomorphisms. John Case, Sanjay Jain, Franco Montagna, Giulia Simi and Andrea Sorbi. In, Bernhard Sch\"olkopf and Manfred Warmuth, editors, Proceedings, 16th Annual Conference on Learning Theory (COLT) and 7th Annual Workshop on Kernel Machines, Proceedings, Washington D. C., pages 699--713. Lecture Notes in Artificial Intelligence 2777. Springer Verlag 2003. Expanded version of the paper.
Learning All Subfunctions of a Function. Sanjay Jain, Efim Kinber and Rolf Wiehagen. In, Bernhard Sch\"olkopf and Manfred Warmuth, editors, 16th Annual Conference on Learning Theory (COLT) and 7th Annual Workshop on Kernel Machines, Proceedings, Washington D. C., pages 714--728. Lecture Notes in Artificial Intelligence 2777. Springer Verlag 2003. Expanded version of the paper.
Classes with Easily Learnable Subclasses. Sanjay Jain, Wolfram Menzel and Frank Stephan. In Nicol\`o Cesa-Bianchi, Masayuki Numao and R\"udiger Reischuk, editors, Algorithmic Learning Theory, 13th International Conference, ALT' 02, L\"ubeck, Germany, November 2002, pages 218--232. Lecture Notes in Artificial Intelligence 2533. Springer Verlag, 2002. Expanded version of the paper.
Learning Recursive Functions Refutably. Sanjay Jain, Efim Kinber, Rolf Wiehagen and Thomas Zeugmann. In, N. Abe, R. Khardon, T. Zeugmann, editors, Algorithmic Learning Theory, 12th International Conference, ALT' 01, Washington D. C., November 2001, pages 283--298. Lecture Notes in Artificial Intelligence, 2225. Springer Verlag 2001. Expanded version of the paper.
Learning Languages in a Union. Sanjay Jain, Yen Kaow Ng, and Tiong Seng Tay In, N. Abe, R. Khardon, T. Zeugmann, editors, Algorithmic Learning Theory, 12th International Conference, ALT' 01, Washington D. C., November 2001, pages 235--250. Lecture Notes in Artificial Intelligence, 2225. Springer Verlag 2001. Expanded version of the paper.
Learning by Switching Type of Information. Sanjay Jain and Frank Stephan. In, N. Abe, R. Khardon, T. Zeugmann, editors, Algorithmic Learning Theory, 12th International Conference, ALT' 01, Washington D. C., November 2001, pages 205--218. Lecture Notes in Artificial Intelligence, 2225. Springer Verlag 2001. Expanded version of the paper.
Learning How to Separate. Sanjay Jain and Frank Stephan. In, N. Abe, R. Khardon, T. Zeugmann, editors, Algorithmic Learning Theory, 12th International Conference, ALT' 01, Washington D. C., November 2001, pages 219--234. Lecture Notes in Artificial Intelligence, 2225. Springer Verlag 2001. Expanded version of the paper.
Intrinsic Complexity of Learning Geometrical Concepts from Positive Data. Sanjay Jain and Efim Kinber. In, David Helmbold and Bob Williamson, editors, Computational Learning Theory, 14th Annual Conference on Computational Learning Theory, COLT 2001, and 5th European Conference on Computational Learning Theory, EuroCOLT 2001, Amsterdam, The Netherlands, pages 177--193. Lecture Notes in Artificial Intelligence, 2111. Springer Verlag 2001. Expanded version of the paper.
Robust Learning -- Rich and Poor. John Case, Sanjay Jain, Frank Stephan and Rolf Wiehagen. In, David Helmbold and Bob Williamson, editors, Computational Learning Theory, 14th Annual Conference on Computational Learning Theory, COLT 2001, and 5th European Conference on Computational Learning Theory, EuroCOLT 2001, Amsterdam, The Netherlands, pages 143--159. Lecture Notes in Artificial Intelligence, 2111. Springer Verlag 2001. Expanded version of the paper.
A Survey of Robust Learning. Sanjay Jain. Invited talk at International Workshop on Quantum Computing and Learning, Sundbyholm, Sweden, 2000. Expanded version of the paper.
Language Learning from Texts: Degrees of Intrinsic Complexity and Their Characterizations. Sanjay Jain, Efim Kinber and Rolf Wiehagen. In Nicolo Cesa-Bianchi and Sally Goldman, editors, Proceedings of the Thirteenth Annual Conference on Computational Learning Theory, Stanford, pages 47--58, Morgan Kaufmann, July 2000. Expanded version of the paper.
On a Generalized Notion of Mistake Bounds. Sanjay Jain and Arun Sharma. In the Proceedings of the Twelfth Annual Conference on Computational Learning Theory, Santa Cruz, pages 249--256, ACM Press, July 1999. Expanded version of the paper.
Mind Change Complexity of Learning Logic Programs. Sanjay Jain, and Arun Sharma. In, P. Fischer and H. U. Simon, editors, Fourth European Conference on Computational Learning Theory, 1999, pages 198--213. Lecture Notes in Artificial Intelligence, 1572. Springer Verlag 1999. Expanded version of the paper.
Costs of General Purpose Learning. John Case, K. J. Chen, and Sanjay Jain. In C. Meinel and S. Tison, editors, STACS 99, 16th Annual Symposium on Theoretical Aspects of Computer Science, Trier, Germnay, 1999, pages 424--433. Lecture Notes in Computer Science 1563. Springer Verlag 1999. Expanded version of the paper.
Predictive Learning Models for Concept Drift. John Case, Sanjay Jain, Susanne Kaufmann, Arun Sharma and Frank Stephan. In M. M. Richter, C. H. Smith, R. Wiehagen, and T. Zeugmann, editors, Algorithmic Learning Theory, 9th International Conference, ALT' 98, Otzenhausen, Germany, 1998, pages 276--290. Lecture Notes in Artificial Intelligence 1501. Springer Verlag, 1998. Expanded version of the paper.
Synthesizing Learners Tolerating Computable Noisy Data. John Case and Sanjay Jain. In M. M. Richter, C. H. Smith, R. Wiehagen, and T. Zeugmann, editors, Algorithmic Learning Theory, 9th International Conference, ALT' 98, Otzenhausen, Germany, 1998, pages 205--219. Lecture Notes in Artificial Intelligence 1501. Springer Verlag, 1998. Expanded version of the paper.
Learning with Refutation. Sanjay Jain. In M. M. Richter, C. H. Smith, R. Wiehagen, and T. Zeugmann, editors, Algorithmic Learning Theory, 9th International Conference, ALT' 98, Otzenhausen, Germany, 1998, pages 291--305. Lecture Notes in Artificial Intelligence 1501. Springer Verlag, 1998. Expanded version of the paper.
Robust Learning Aided by Context. John Case, Sanjay Jain, Matthias Ott, Arun Sharma and Frank Stephan. In the Proceedings of the Eleventh Annual Conference on Computational Learning Theory, Wisconsin-Madison, pages 44--55. ACM Press, July 1998. Expanded version of the paper.
On the Power of Learning Robustly Sanjay Jain, Carl Smith, and Rolf Wiehagen. In the Proceedings of the Eleventh Annual Conference on Computational Learning Theory, Wisconsin-Madison, pages 187--197. ACM Press, July 1998. Expanded version of the paper.
Learning of R.E. languages from Good Examples. Sanjay Jain, Steffen Lange, and Jochen Nessel. In Ming Li and Akira Maruoka, editors, Algorithmic Learning Theory, 8th International Workshop, ALT' 97, Sendai, Japan, 1997, pages 32--47. Lecture Notes in Artificial Intelligence 1316. Springer Verlag, 1997. Expanded version of the paper.
Synthesizing Noise-Tolerant Language Learners. John Case, Sanjay Jain, and Arun Sharma. In Ming Li and Akira Maruoka, editors, Algorithmic Learning Theory, 8th International Workshop, ALT' 97, Sendai, Japan, 1997, pages 228--243. Lecture Notes in Artificial Intelligence 1316. Springer Verlag, 1997. Expanded version of the paper.
Learning Concepts Incrementally With Bounded Data Mining. John Case, Sanjay Jain, Steffen Lange, and Thomas Zeugmann. In Automata Induction, Grammatical Inference, and Language Acquisition: Workshop at the Fourteenth International Conference on Machine Learning (ICML-97), Nashville, Tennessee, July 1997. Expanded version of the paper.
Control Structures in Hypothesis Spaces: The Influence on Learning. John Case, Sanjay Jain, and Mandayam Suraj. In S. Ben-David, editor, Third European Conference on Computational Learning Theory' 97, Jerusalem, Israel, pages 286--300. Lecture Notes in Artificial Intelligence 1208, Springer-Verlag, 1997. Expanded version of the paper.
Ordinal Mind Change Complexity of Language Identification. Andris Ambainis, Sanjay Jain, and Arun Sharma. In S. Ben-David, editor, Third European Conference on Computational Learning Theory' 97, Jerusalem, Israel, pages 301--315. Lecture Notes in Artificial Intelligence 1208, Springer-Verlag, 1997. Expanded version of the paper.
Vacillatory and BC learning on noisy data. John Case, Sanjay Jain and Frank Stephan. In S. Arikawa and A. Sharma, editors, Algorithmic Learning Theory, Seventh International Workshop, ALT' 96, Sydney, Australia, pages 285--298. Lecture Notes in Artificial Intelligence 1160. Springer Verlag, 1996. Expanded version of the paper.
On learning and co-learning of minimal programs. Sanjay Jain, Efim Kinber and Rolf Wiehagen. In S. Arikawa and A. Sharma, editors, Algorithmic Learning Theory, Seventh International Workshop, ALT' 96, Sydney, Australia, pages 242--255. Lecture Notes in Artificial Intelligence 1160. Springer Verlag, 1996. Expanded version of the paper.
Team Learning of Recursive Languages. Sanjay Jain and Arun Sharma. In N. Foo and R. Goebel, editors, Proceedings of the Fourth Pacific Rim International Conference on Artificial Intelligence, Cairns, Australia, pages 324--335. Lecture Notes in Artificial Intelligence 1114. Springer-Verlag, 1996. Expanded version of the paper.
Elementary Formal Systems, Intrinsic Complexity and Procrastination. Sanjay Jain and Arun Sharma. In the Proceedings of the Ninth Annual Conference on Computational Learning Theory, Desenzano del Garda, Italy, pages 181--192. ACM Press, 1996. Expanded version of the paper.
Synthesising Enumeration Techniques for Language Learning. Ganesh Baliga, John Case and Sanjay Jain. In the Proceedings of the Ninth Annual Conference on Computational Learning Theory, Desenzano del Garda, Italy, pages 169--180. ACM Press 1996. Expanded version of the paper.
Branch and Bound on the Network Model. Sanjay Jain. In Thiagarajan, P. S., editor, Foundations of Software Technology and Theoretical Computer Science, Fifteenth Conference, Banglore, India, pages 11--21. Lecture Notes in Computer Science 1026. Springer Verlag, December 1995. Expanded version of the paper.
Machine Induction Without Revolutionary Paradigm Shifts. John Case, Sanjay Jain and Arun Sharma. In K. P. Jantke, T. Shinohara, T. Zeugmann, editors, Sixth International Workshop on Algorithmic Learning Theory, Fukuoka, Japan, pages 153--168. Lecture Notes in Artificial Intelligence 997. Springer Verlag, October 1995. Expanded version of the paper.
Team Learning of Formal Languages. Sanjay Jain and Arun Sharma. In Twelfth International Conference on Machine Learning: Workshop on Agents that Learn from Other Agents. Tahoe City, California, U.S.A. July 1995. Expanded version of the paper.
The Structure of Intrinsic Complexity of Learning. Sanjay Jain and Arun Sharma. In Paul Vitanyi, editor, Computational Learning Theory, Second European Conference, EuroCOLT'95, Barcelona, Spain, pages 169--181. Lecture Notes in Artificial Intelligence 904. Springer Verlag, March 1995. Expanded version of the paper.
Kolmogorov Numberings and Minimal Identification. Rusins Freivalds and Sanjay Jain. In Paul Vitanyi, editor, Computational Learning Theory, Second European Conference, EuroCOLT'95, Barcelona, Spain, pages 182--195. Lecture Notes in Artificial Intelligence 904. Springer Verlag, March 1995. Expanded version of the paper.
Program Synthesis in the Presence of Infinite Number of Inaccuracies. Sanjay Jain. In S. Arikawa and K. P. Jantke, editors, Algorithmic Learning Theory, Proceedings of the 4th International Workshop on Analogical and Inductive Inference, AII'94 and 5th International Workshop on Algorithmic Learning Theory, ALT'94, Reinhardsbrunn Castle, Germany, pages 333--348. Lecture Notes in Artificial Intelligence 872. Springer Verlag, October 1994. Expanded version of the paper.
On monotonic strategies for learning r.e. languages. Sanjay Jain and Arun Sharma. In S. Arikawa and K. P. Jantke, editors, Algorithmic Learning Theory, Proceedings of the 4th International Workshop on Analogical and Inductive Inference, AII'94 and 5th International Workshop on Algorithmic Learning Theory, ALT'94, Reinhardsbrunn Castle, Germany, pages 349--364. Lecture Notes in Artificial Intelligence 872. Springer Verlag, October 1994. Expanded version of the paper.
On the Intrinsic Complexity of Language Identification. Sanjay Jain and Arun Sharma. In the Proceedings of the Seventh Annual Conference on Computational Learning Theory, New Brunswick, New Jersey, pages 278--286. ACM Press, July 1994. Expanded version of the paper.
On Aggregating Teams of Learning Machines. Sanjay Jain and Arun Sharma. In Jantke, K. P., Kobayashi, S., Tomita, E., Yokomari, T., editors, Proceedings of the Fourth International Workshop on Algorithmic Learning Theory, Tokyo, Japan, pages 150--163. Lecture Notes in Artificial Intelligence 744. Springer Verlag, November 1993. Expanded version of the paper.
Probability is More Powerful than Team for Language Identification from Positive Data. Sanjay Jain and Arun Sharma. In the Proceedings of the Sixth Annual Conference on Computational Learning Theory, Santa Cruz, California, pages 192--198. ACM Press, July 1993. Expanded version of the paper.
On characterizing language identification in terms of computable numbering. Sanjay Jain and Arun Sharma. Presented at the Fifth Asian Logic Conference, Singapore, June 1993. Expanded version of the paper.
Language Learning with Some Negative Information. Ganesh Baliga, John Case and Sanjay Jain. In Enjalbert, P., Finkel, A., Wagner, K. W., editors, Proceedings of the Symposium on Theoretical Aspects of Computer Science, W\"{u}rzburg, Germany, pages 672--681. Lecture Notes in Computer Science 665. Springer Verlag, February 1993. Expanded version of the paper.
Prudence in Vacillatory Language Identification. Sanjay Jain and Arun Sharma. In Doshita, S., Furukawa, K., Jantke, K. P. and Nishida, T., editors, Proceedings of the Third Workshop on Algorithmic Learning Theory, Tokyo, Japan, pages 159--168. Lecture Notes in Artificial Intelligence 743. Springer Verlag, October 1992. Expanded version of the paper.
Learning from Multiple Sources of Inaccurate Data. Ganesh Baliga, Sanjay Jain and Arun Sharma. In K. P. Jantke, editor, Analogical and Inductive Inference, International Workshop AII'92, Dagstuhl Castle, Germany, proceedings, pages 108--128. Lecture Notes in Artificial Intelligence 642. Springer Verlag, October 1992. Expanded version of the paper.
Strong Separation of Learning Classes. John Case, Keh-Jiann Chen and Sanjay Jain. In K. P. Jantke, editor, Analogical and Inductive Inference, International Workshop AII'92, Dagstuhl Castle, Germany, proceedings, pages 129--139. Lecture Notes in Artificial Intelligence 642. Springer Verlag, October 1992. Expanded version of the paper.
On Learning Limiting Programs. John Case, Sanjay Jain and Arun Sharma. In the Proceedings of the Fifth Annual Workshop on Computational Learning Theory, Pittsburgh, Pennsylvania, pages 193--202. ACM Press, July 1992. Expanded version of the paper.
Banishing Robust Turing Completeness. Lane Hemachandra, Sanjay Jain and Nikolai Vereshchagin. In Logical Foundations of Computer Science, Tver, Russia, pages 186--197. Lecture Notes in Computer Science 620. Springer Verlag, July 1992. Expanded version of the paper.
Machine Learning of Higher Order Programs. Ganesh Baliga, John Case, Sanjay Jain and Mandayam Suraj. In Logical Foundations of Computer Science, Tver, Russia, pages 9--20. Lecture Notes in Computer Science 620. Springer Verlag, July 1992. Expanded version of the paper.
Complexity Issues for Vacillatory Function Identification. John Case, Sanjay Jain and Arun Sharma. In S. Biswas and K. V. Nori, editors, Foundations of Software Technology and Theoretical Computer Science, Eleventh Conference, New Delhi, India, pages 121--140. Lecture Notes in Computer Science 560. Springer Verlag, December 1991. Expanded version of the paper.
Restrictions on Grammar Size in Language Identification. Sanjay Jain and Arun Sharma. In David Powers and Larry Reeker, editors, Proceedings MLNLO'91, Machine Learning of Natural Language and Ontology, Stanford University, California, pages 87--92. Document D91--09, DFKI: Kaiserslautern FRG, March 1991. Expanded version of the paper.
Approximate Inference and Scientific Method. Mark Fulk and Sanjay Jain. In S. Arikawa, S. Goto, S. Ohsuga and T. Yokomori, editors, Proceedings of the First International Workshop on Algorithmic Learning Theory, Tokyo, Japan, pages 256--265. Japanese Society for Artificial Intelligence, October 1990. Expanded version of the paper.
Anomalous Learning Helps Succinctness. John Case, Sanjay Jain and Arun Sharma. In S. Arikawa, S. Goto, S. Ohsuga and T. Yokomori, editors, Proceedings of the First International Workshop on Algorithmic Learning Theory, Tokyo, Japan, pages 282--288. Japanese Society for Artificial Intelligence, October 1990. Expanded version of the paper.
Learning with the Knowledge of an Upper Bound on Program Size. Sanjay Jain and Arun Sharma. Presented at the Workshop on Computational Learning Theory and Natural Learning Systems, September 1990. Expanded version of the paper.
Finite Learning by a Team. Sanjay Jain and Arun Sharma. In M. Fulk and J. Case, editors, Proceedings of the Third Annual Workshop on Computational Learning Theory, Rochester, New York, pages 163--177. Morgan Kaufmann Publishers Inc., August 1990. Expanded version of the paper.
Language Learning by a Team. Sanjay Jain and Arun Sharma. In M. S. Paterson, editor, Automata, Languages and Programming, 17th International Colloquium, Warwick University, England, pages 153--166. Lecture Notes in Computer Science 443. Springer Verlag, July 1990. Expanded version of the paper.
Characterizing Language Learning by Standardizing Operations. Sanjay Jain and Arun Sharma. In S. G. Akl, F. Fiala and W. W. Koczkodaj, editors, Advances in Computing and Information, Proceedings of the International Conference on Computing and Information, ICCI'90, Niagara Falls, Canada, pages 144--148. Canadian Scholars' Press, Inc., Toronto, May 1990. Expanded version of the paper.
Hypothesis Formation and Language Acquisition with an Infinitely-Often Correct Teacher. Sanjay Jain and Arun Sharma. In R. Parikh, editor, Theoretical Aspects of Reasoning about Knowledge, Proceedings of the Third Conference (TARK 1990), Pacific Grove, California, pages 225--239. Morgan Kaufmann Publishers Inc., March 1990. Expanded version of the paper.
On the Limitations of Locally Robust Positive Reductions. Lane Hemachandra and Sanjay Jain. In C. E. Veni Madhavan, editor, Foundations of Software Technology and Theoretical Computer Science, Ninth Conference, Bangalore, India, pages 193--203. Lecture Notes in Computer Science 405. Springer Verlag, December 1989. Expanded version of the paper.
Convergence to Nearly Minimal Size Grammars by Vacillating Learning Machines. John Case, Sanjay Jain and Arun Sharma. In R. Rivest, D. Haussler and M. K. Warmuth, editors, Proceedings of the Second Annual Workshop on Computational Learning Theory, Santa Cruz, California, pages 189--199. Morgan Kaufmann Publishers Inc., August 1989. Expanded version of the paper.
Learning in the Presence of Inaccurate Information. Mark Fulk and Sanjay Jain. In R. Rivest, D. Haussler and M. K. Warmuth, editors, Proceedings of the Second Annual Workshop on Computational Learning Theory, Santa Cruz, California, pages 175--188. Morgan Kaufmann Publishers Inc., August 1989. Expanded version of the paper.
Crowd Control: Coordinating Processes in Parallel. Thomas J. LeBlanc and Sanjay Jain. In S. K. Sahni, editor, Proceedings of the 1987 International Conference on Parallel Processing, University Park, Pennsylvania, pages 81--84. The Pennsylvania State University Press, University Park and London, August 1987.
Qualitative Optimization: An AI Approach to Policy Design in System Dynamics. S. Ghose, P. P. Chakrabarti, Sanjay Jain and R. K. Dubey. In Proceedings of the Second National Conference on System Dynamics, Benares, India, Jan 15--17 1987.