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[2893] S. Jain and E. Kinber. Inductive inference of languages from samplings. In M. Hutter, F. Stephan, V. Vovk, and T. Zeugmann, editors, Algorithmic Learning Theory, 21th International Conference, ALT 2010, Canberra, Australia, October 6-8, 2010, Proceedings, volume 6331 of Lecture Notes in Artificial Intelligence, pages 330–344, Berlin, Heidelberg, New York, 2010. Springer.

[2894] S. Jain and E. Kinber. Automatic learning from positive data and negative counterexamples. In N. H. Bshouty, G. Stoltz, N. Vayatis, and T. Zeugmann, editors, Algorithmic Learning Theory, 23rd International Conference, ALT 2012, Lyon, France, October 29–31, 2012, Proceedings, volume 7568 of Lecture Notes in Artificial Intelligence, pages 66–80, Berlin, Heidelberg, New York, 2012. Springer.

[2895] S. Jain and E. Kinber. Mind change speed-up for learning languages from positive data. Theoret. Comput. Sci., 489-490:37–47, 2013.

[2896] S. Jain and E. Kinber. Parallel learning of automatic classes of languages. In P. Auer, A. Clark, T. Zeugmann, and S. Zilles, editors, Algorithmic Learning Theory, 25th International Conference, ALT 2014, Bled, Slovenia, October 8–10, 2014, Proceedings, volume 8776 of Lecture Notes in Artificial Intelligence, pages 70–84, Berlin, Heidelberg, New York, 2014. Springer.

[2897] S. Jain and E. Kinber. Intrinsic complexity of partial learning. In R. Ortner, H. U. Simon, and S. Zilles, editors, Algorithmic Learning Theory, 27th International Conference, ALT 2016, Bari, Italy, October 19-21, 2016, Proceedings, volume 9925 of Lecture Notes in Artificial Intelligence, pages 174–188. Springer, 2016.

[2898] S. Jain and E. Kinber. Parallel learning of automatic classes of languages. Theoret. Comput. Sci., 650:25–44, 2016. Special Issue: Algorithmic Learning Theory.

[2899] S. Jain, E. Kinber, S. Lange, R. Wiehagen, and T. Zeugmann. Learning languages and functions by erasing. Theoret. Comput. Sci., 241(1-2):143–189, 2000. Special issue for ALT ’96.

[2900] S. Jain, E. Kinber, C. Papazian, C. Smith, and R. Wiehagen. On the intrinsic complexity of learning recursive functions. Inform. Comput., 184(1):45–70, 2003.

[2901] S. Jain, E. Kinber, and R. Wiehagen. On learning and co-learning of minimal programs. In Algorithmic Learning Theory, 7th International Workshop, ALT ’96, Sydney, Australia, October 1996, Proceedings, volume 1160 of Lecture Notes in Artificial Intelligence, pages 242–255. Springer, 1996.

[2902] S. Jain, E. Kinber, and R. Wiehagen. Language learning from texts: Degrees of instrinsic complexity and their characterizations. In Proc. 13th Annu. Conference on Comput. Learning Theory, pages 47–58. Morgan Kaufmann, San Francisco, 2000.

[2903] S. Jain, E. Kinber, and R. Wiehagen. Language learning from texts: Degrees of intrinsic complexity and their characterizations. J. Comput. Syst. Sci., 63(3):305–354, 2001.

[2904] S. Jain, E. Kinber, and R. Wiehagen. Learning all subfunctions of a function. In Learning Theory and Kernel Machines, 16th Annual Conference on Learning Theory and 7th Kernel Workshop, COLT/Kernel 2003, Washington, DC, USA, August 24-27, 2003, Proceedings, volume 2777 of Lecture Notes in Artificial Intelligence, pages 714–728. Springer, 2003.

[2905] S. Jain, E. Kinber, and R. Wiehagen. Learning all subfunctions of a function. Inform. Comput., 192(2):185–215, 2004.

[2906] S. Jain, E. Kinber, R. Wiehagen, and T. Zeugmann. Learning recursive functions refutably. In Algorithmic Learning Theory, 12th International Conference, ALT 2001, Washington, DC, USA, November 25–28, 2001, Proceedings, volume 2225 of Lecture Notes in Artificial Intelligence, pages 283–298. Springer, 2001.

[2907] S. Jain, E. Kinber, R. Wiehagen, and T. Zeugmann. On learning of functions refutably. Theoret. Comput. Sci., 298(1):111–143, 2003.

[2908] S. Jain and E. B. Kinber. Intrinsic complexity of learning geometrical concepts from positive data. J. Comput. Syst. Sci., 67(3):546–607, 2003.

[2909] S. Jain, T. Kötzing, J. Ma, and F. Stephan. On the role of update constraints and text-types in iterative learning. In P. Auer, A. Clark, T. Zeugmann, and S. Zilles, editors, Algorithmic Learning Theory, 25th International Conference, ALT 2014, Bled, Slovenia, October 8–10, 2014, Proceedings, volume 8776 of Lecture Notes in Artificial Intelligence, pages 55–69, Berlin, Heidelberg, New York, 2014. Springer.

[2910] S. Jain, T. Kötzing, and F. Stephan. Enlarging learnable classes. In N. H. Bshouty, G. Stoltz, N. Vayatis, and T. Zeugmann, editors, Algorithmic Learning Theory, 23rd International Conference, ALT 2012, Lyon, France, October 29–31, 2012, Proceedings, volume 7568 of Lecture Notes in Artificial Intelligence, pages 36–50, Berlin, Heidelberg, New York, 2012. Springer.

[2911] S. Jain, T. Kötzing, and F. Stephan. Enlarging learnable classes. Inform. Comput., 251:194– 207, 2016.

[2912] S. Jain, S. Lange, S. E. Moelius III, and S. Zilles. Incremental learning with temporary memory. Theoret. Comput. Sci., 411(29-30):2757–2772, 2010. Special issue for ALT 2008.

[2913] S. Jain, S. Lange, and J. Nessel. Learning of r.e. languages from good examples. In Algorithmic Learning Theory, 8th International Workshop, ALT ’97, Sendai, Japan, October 1997, Proceedings, volume 1316 of Lecture Notes in Artificial Intelligence, pages 32–47. Springer, 1997.

[2914] S. Jain, S. Lange, and J. Nessel. On the learnability of recursively enumerable languages from good examples. Theoret. Comput. Sci., 261(1):3–29, 2001. Special issue for ALT ’97.

[2915] S. Jain, S. Lange, and S. Zilles. Gold-style and query learning under various constraints on the target class. In Algorithmic Learning Theory, 16th International Conference, ALT 2005, Singapore, October 2005, Proceedings, volume 3734 of Lecture Notes in Artificial Intelligence, pages 226–240. Springer, Oct. 2005.

[2916] S. Jain, S. Lange, and S. Zilles. Towards a better understanding of incremental learning. In Algorithmic Learning Theory, 17th International Conference, ALT 2006, Barcelona, Spain, October 2006, Proceedings, volume 4264 of Lecture Notes in Artificial Intelligence, pages 169–183. Springer, Oct. 2006.

[2917] S. Jain, S. Lange, and S. Zilles. A general comparison of language learning from examples and from queries. Theoret. Comput. Sci., 387(1):51–66, 2007. Special issue for ALT 2005.

[2918] S. Jain, S. Lange, and S. Zilles. Some natural conditions on incremental learning. Inform. Comput., 205(11):1671–1684, 2007.

[2919] S. Jain, Q. Luo, P. Semukhin, and F. Stephan. Uncountable automatic classes and learning. In R. Gavaldà, G. Lugosi, T. Zeugmann, and S. Zilles, editors, Algorithmic Learning Theory, 20th International Conference, ALT 2009, Porto, Portugal, October 2009, Proceedings, volume 5809 of Lecture Notes in Artificial Intelligence, pages 293–307, Berlin/Heidelberg, 2009. Springer.

[2920] S. Jain, Q. Luo, P. Semukhin, and F. Stephan. Uncountable automatic classes and learning. Theoret. Comput. Sci., 412(19):1805–1820, 2011.

[2921] S. Jain, Q. Luo, and F. Stephan. Learnability of automatic classes. J. Comput. Syst. Sci., 78(6):1910–1927, 2012.

[2922] S. Jain, J. Ma, and F. Stephan. Priced learning. In K. Chaudhuri, C. Gentile, and S. Zilles, editors, Algorithmic Learning Theory, 26th International Conference, ALT 2015, Banff, AB, Canada, October 4–6, 2015, Proceedings, volume 9355 of Lecture Notes in Artificial Intelligence, pages 41–55, Berlin, Heidelberg, New York, 2015. Springer.

[2923] S. Jain, E. Martin, and F. Stephan. Absolute versus probabilistic classification in a logical setting. In Algorithmic Learning Theory, 16th International Conference, ALT 2005, Singapore, October 2005, Proceedings, volume 3734 of Lecture Notes in Artificial Intelligence, pages 327–342. Springer, Oct. 2005.

[2924] S. Jain, E. Martin, and F. Stephan. Absolute versus probabilistic classification in a logical setting. Theoret. Comput. Sci., 397(1-3):114–128, 2008. Special issue Forty Years of Inductive Inference: Dedicated to the 60th Birthday of Rolf Wiehagen.

[2925] S. Jain, E. Martin, and F. Stephan. Learning and classifying. In J. Kivinen, C. Szepesvári, E. Ukkonen, and T. Zeugmann, editors, Algorithmic Learning Theory, 22nd International Conference, ALT 2011, Aalto University, Espoo, Finland October 5–7, 2011, Proceedings, volume 6925 of Lecture Notes in Artificial Intelligence, pages 70–83, Berlin, Heidelberg, New York, 2011. Springer.

[2926] S. Jain, E. Martin, and F. Stephan. Robust learning of automatic classes of languages. In J. Kivinen, C. Szepesvári, E. Ukkonen, and T. Zeugmann, editors, Algorithmic Learning Theory, 22nd International Conference, ALT 2011, Aalto University, Espoo, Finland October 5–7, 2011, Proceedings, volume 6925 of Lecture Notes in Artificial Intelligence, pages 55–69, Berlin, Heidelberg, New York, 2011. Springer.

[2927] S. Jain, E. Martin, and F. Stephan. Learning and classifying. Theoret. Comput. Sci., 482:73–85, 2013.

[2928] S. Jain, E. Martin, and F. Stephan. Robust learning of automatic classes of languages. J. Comput. Syst. Sci., 80(4):777–795, 2014.

[2929] S. Jain, W. Menzel, and F. Stephan. Classes with easily learnable subclasses. In Algorithmic Learning Theory, 13th International Conference, ALT 2002, Lübeck, Germany November 2002, Proceedings, volume 2533 of Lecture Notes in Artificial Intelligence, pages 218–232. Springer, 2002.

[2930] S. Jain, W. Menzel, and F. Stephan. Classes with easily learnable subclasses. Inform. Comput., 190(1):81–99, 2004.

[2931] S. Jain, S. E. Moelius III, and S. Zilles. Learning without coding. Theoret. Comput. Sci., 473:124–148, 2013. Special Issue on Learning Theory.

[2932] S. Jain, R. Munos, F. Stephan, and T. Zeugmann, editors. Algorithmic Learning Theory, 24th International Conference, ALT 2013, Singapore, October 6–9, 2013, Proceedings, volume 8139 of Lecture Notes in Artificial Intelligence, Berlin, Heidelberg, New York, Oct. 2013. Springer.

[2933] S. Jain, R. Munos, F. Stephan, and T. Zeugmann. Editors’ introduction. In S. Jain, R. Munos, F. Stephan, and T. Zeugmann, editors, Algorithmic Learning Theory, 24th International Conference, ALT 2013, Singapore, October 6–9, 2013, Proceedings, volume 8139 of Lecture Notes in Artificial Intelligence, pages 1–12, Berlin, Heidelberg, New York, 2013. Springer.

[2934] S. Jain, R. Munos, F. Stephan, and T. Zeugmann. Guest Editors’ foreword. Theoret. Comput. Sci., 620:1–3, 2016. Special Issue: Algorithmic Learning Theory.

[2935] S. Jain and J. Nessel. Some independence results for control structures in complete numberings. J. Symbolic Logic, 66(1):357–382, 2001.

[2936] S. Jain, Y. K. Ng, and T. S. Tay. Learning languages in a union. In Algorithmic Learning Theory, 12th International Conference, ALT 2001, Washington, DC, USA, November 25– 28, 2001, Proceedings, volume 2225 of Lecture Notes in Artificial Intelligence, pages 235–250. Springer, 2001.

[2937] S. Jain, Y. K. Ng, and T. S. Tay. Learning languages in a union. J. Comput. Syst. Sci., 73(1):89–108, 2007.

[2938] S. Jain, Y. S. Ong, and F. Stephan. Regular patterns, regular languages and context-free languages. Information Processing Letters, 110(24):1114–1119, 2010.

[2939] S. Jain, D. Osherson, J. S. Royer, and A. Sharma. Systems that Learn: An Introduction to Learning Theory, second edition. MIT Press, Cambridge, Massachusetts, 1999.

[2940] S. Jain and A. Sharma. Knowledge of an upper bound on grammar size helps language learning. Technical Report 283, University of Rochester, 1989.

[2941] S. Jain and A. Sharma. Recursion theoretic characterizations of language learning. Technical Report 281, University of Rochester, 1989.

[2942] S. Jain and A. Sharma. Finite learning by a team. In Proceedings of the Third Annual Workshop on Computational Learning Theory, pages 163–177, San Mateo, CA, 1990. Morgan Kaufmann.

[2943] S. Jain and A. Sharma. Hypothesis formation and language acquisition with an infinitely often correct teacher. In Proc. of the Third Conference on Theoretical Aspects of Reasoning About Knowledge, pages 225–239. Morgan Kaufmann, Inc., Mar. 1990.

[2944] S. Jain and A. Sharma. Language learning by a “team” (extended abstract). In Automata, Languages and Programming, 17th International Colloquium Warwick University, England, July 16-20, 1990 Proceedings, volume 443 of Lecture Notes in Computer Science, pages 153–166. Springer-Verlag, 1990.

[2945] S. Jain and A. Sharma. Program size restrictions in inductive learning. Technical Report 90-06, University of Delaware, Newark, Delaware, 1990.

[2946] S. Jain and A. Sharma. Learning in the presence of partial explanations. Inform. Comput., 95(2):162–191, 1991.

[2947] S. Jain and A. Sharma. Restrictions on grammar size in language identification. In Proc. MLNLO’91, Machine Learning of Natural Language and Ontology, Stanford University, California. Document D91-09, DFKI: Kaiserslautern FRG, 1991, pages 87–92, Mar. 1991.

[2948] S. Jain and A. Sharma. Computational limits on team identification of languages. Technical Report 9301, School of Computer Science and Engineering; University of New South Wales, 1993.

[2949] S. Jain and A. Sharma. Learning with the knowledge of an upper bound on program size. Inform. Comput., 102(1):118–166, 1993.

[2950] S. Jain and A. Sharma. On the non-existence of maximal inference degrees for language identification. Inform. Proc. Lett., 47(2):81–88, 1993.

[2951] S. Jain and A. Sharma. Probability is more powerful than team for language identification from positive data. In Proceedings of the Sixth Annual ACM Conference on Computational Learning Theory, pages 192–198, New York, New York, 1993. ACM Press.

[2952] S. Jain and A. Sharma. Characterizing language identification by standardizing operations. J. of Comput. Syst. Sci., 49(1):96–107, 1994.

[2953] S. Jain and A. Sharma. On monotonic strategies for learning r.e. languages. In Algorithmic Learning Theory, 4th International Workshop on Analogical and Inductive Inference, AII ’94, 5th International Workshop on Algorithmic Learning Theory, ALT ’94, Reinhardsbrunn Castle, Germany, October 1994, Proceedings, volume 872 of Lecture Notes in Artificial Intelligence, pages 349–364. Springer-Verlag, 1994.

[2954] S. Jain and A. Sharma. On the intrinsic complexity of language identification. In Proc. 7th Annu. ACM Conf. on Comput. Learning Theory, pages 278–286, New York, NY, 1994. ACM Press.

[2955] S. Jain and A. Sharma. Program size restrictions in computational learning. Theoret. Comput. Sci., 127(2):351–386, 1994.

[2956] S. Jain and A. Sharma. On aggregating teams of learning machines. Theoret. Comput. Sci., 137(1):85–108, 1995. Special issue for ALT ’93.

[2957] S. Jain and A. Sharma. On identification by teams and probabilistic machines. In Algorithmic Learning for Knowledge-Based Systems, volume 961 of Lecture Notes in Artificial Intelligence, pages 108–145. Springer, 1995.

[2958] S. Jain and A. Sharma. Prudence in vacillatory language identification. Math. Syst. Theory, 28(3):267–279, 1995.

[2959] S. Jain and A. Sharma. The structure of intrinsic complexity of learning. In Computational Learning Theory, Second European Conference, EuroCOLT ’95, Barcelona, Spain, March 1995, Proceedings, volume 904 of Lecture Notes in Artificial Intelligence, pages 169–181. Springer, 1995.

[2960] S. Jain and A. Sharma. Computational limits on team identification of languages. Inform. Comput., 130(1):19–60, 1996.

[2961] S. Jain and A. Sharma. The intrinsic complexity of language identification. J. of Comput. Syst. Sci., 52(3):393–402, 1996.

[2962] S. Jain and A. Sharma. Team learning of recursive languages. In Proceedings of the Fourth Pacific Rim International Conference on Artificial Intelligence, Cairns, Australia, volume 1114 of Lecture Notes in Artificial Intelligence, pages 324–335. Springer, 1996.

[2963] S. Jain and A. Sharma. Characterizing language learning in terms of computable numberings. Annals of Pure and Applied Logic, 84(1):51–72, 1997.

[2964] S. Jain and A. Sharma. Elementary formal systems, intrinsic complexity, and procrastination. Inform. Comput., 132(1):65–84, 1997. first in Colt ’96.

[2965] S. Jain and A. Sharma. The structure of intrinsic complexity of learning. Journal of Symbolic Logic, 62(4):1187–1201, 1997.

[2966] S. Jain and A. Sharma. Generalization and specialization strategies for learning r.e. languages. Annals of Mathematics and Artificial Intelligence, 23(1/2):1–26, 1998. Special issue for AII ’94 and ALT ’94.

[2967] S. Jain and A. Sharma. Mind change complexity of learning logic programs. In Computational Learning Theory, 4th European Conference, EuroCOLT ’99, Nordkirchen, Germany, March 29-31, 1999, Proceedings, volume 1572 of Lecture Notes in Artificial Intelligence, pages 198–213. Springer, 1999.

[2968] S. Jain and A. Sharma. On a generalized notion of mistake bounds. In Proceedings of the Twelfth Annual Conference on Computational Learning Theory, July 6th-9th, 1999, Santa Cruz, California, pages 249–256, New York, NY, 1999. ACM Press.

[2969] S. Jain and A. Sharma. Team learning of computable languages. Theory of Computing Systems, 33(1):35–58, 2000.

[2970] S. Jain and A. Sharma. On a generalized notion of mistake bounds. Inform. Comput., 166(2):156–166, May 2001.

[2971] S. Jain and A. Sharma. Mind change complexity of learning logic programs. Theoret. Comput. Sci., 284(1):143–160, 2002.

[2972] S. Jain, A. Sharma, and J. Case. Convergence to nearly minimal size grammars by vacillating learning machines. In Proceedings of the Second Annual Workshop on Computational Learning Theory, pages 189–199, San Mateo, CA, 1989. Morgan Kaufmann.

[2973] S. Jain, A. Sharma, and M. Velauthapillai. Finite identification of functions by teams with success ratio \frac{1}{2} and above. Inform. Comput., 121(2):201–213, 1995.

[2974] S. Jain, H. U. Simon, and E. Tomita, editors. Algorithmic Learning Theory, 16th International Conference, ALT 2005, Singapore, October 2005, Proceedings, volume 3734 of Lecture Notes in Artificial Intelligence, Berlin/Heidelberg, Oct. 2005. Springer.

[2975] S. Jain, H. U. Simon, and E. Tomita. Editors’ introduction. In Algorithmic Learning Theory, 16th International Conference, ALT 2005, Singapore, October 2005, Proceedings, volume 3734 of Lecture Notes in Artificial Intelligence, pages 1–9. Springer, Oct. 2005.

[2976] S. Jain, C. Smith, and R. Wiehagen. On the power of learning robustly. In Proceedings of the Eleventh Annual Conference on Computational Learning Theory, pages 187–197, New York, NY, 1998. ACM Press.

[2977] S. Jain, C. Smith, and R. Wiehagen. Robust learning is rich. J. Comput. Syst. Sci., 62(1):178–212, 2001.

[2978] S. Jain and F. Stephan. Learning by switching type of information. In Algorithmic Learning Theory, 12th International Conference, ALT 2001, Washington, DC, USA, November 25– 28, 2001, Proceedings, volume 2225 of Lecture Notes in Artificial Intelligence, pages 205–218. Springer, 2001.

[2979] S. Jain and F. Stephan. Learning how to separate. In Algorithmic Learning Theory, 12th International Conference, ALT 2001, Washington, DC, USA, November 25–28, 2001, Proceedings, volume 2225 of Lecture Notes in Artificial Intelligence, pages 219–234. Springer, 2001.

[2980] S. Jain and F. Stephan. Learning by switching type of information. Inform. Comput., 185(1):89–104, 2003.

[2981] S. Jain and F. Stephan. Learning how to separate. Theoret. Comput. Sci., 313(2):209–228, 2004. Special issue for ALT 2001.

[2982] S. Jain and F. Stephan. Some recent results in U-shaped learning. In Theory and Applications of Models of Computation, Third International Conference, TAMC 2006, Beijing, China, May 2006, Proceedings, volume 3959 of Lecture Notes in Computer Science, pages 421–431, Berlin, 2006. Springer.

[2983] S. Jain and F. Stephan. Learning in friedberg numberings. In Algorithmic Learning Theory, 18th International Conference, ALT 2007, Sendai, Japan, October 2007, Proceedings, volume 4754 of Lecture Notes in Artificial Intelligence, pages 79–93, Berlin, Oct. 2007. Springer.

[2984] S. Jain and F. Stephan. Mitotic classes. In Learning Theory, 20th Annual Conference on Learning Theory, COLT 2007, San Diego, CA, USA; June 13-15, 2007, Proceedings, volume 4539 of Lecture Notes in Artificial Intelligence, pages 218–232, Berlin, 2007. Springer.

[2985] S. Jain and F. Stephan. Mitotic classes in inductive inference. SIAM J. Comput., 38(4):1283– 1299, 2008.

[2986] S. Jain and F. Stephan. Numberings optimal for learning. In Algorithmic Learning Theory, 19th International Conference, ALT 2008, Budapest, Hungary, October 2008, Proceedings, volume 5254 of Lecture Notes in Artificial Intelligence, pages 434–448, Berlin, Oct. 2008. Springer.

[2987] S. Jain and F. Stephan. Complexity of inductive inference. In C. Sammut and G. I. Webb, editors, Encyclopedia of Machine Learning, pages 198–201. Springer, New York, 2010.

[2988] S. Jain and F. Stephan. Inductive inference. In C. Sammut and G. I. Webb, editors, Encyclopedia of Machine Learning, pages 523–528. Springer, New York, 2010.

[2989] S. Jain and F. Stephan. Query-based learning. In C. Sammut and G. I. Webb, editors, Encyclopedia of Machine Learning, pages 820–822. Springer, New York, 2010.

[2990] S. Jain, F. Stephan, and S. Terwijn. Counting extensional differences in BC-learning. Inform. Comput., 188(1):127–142, 2004.

[2991] S. Jain, F. Stephan, and N. Ye. Prescribed learning of R.E. classes. In Algorithmic Learning Theory, 18th International Conference, ALT 2007, Sendai, Japan, October 2007, Proceedings, volume 4754 of Lecture Notes in Artificial Intelligence, pages 64–78, Berlin, Oct. 2007. Springer.

[2992] S. Jain, F. Stephan, and N. Ye. Learning from streams. In R. Gavaldà, G. Lugosi, T. Zeugmann, and S. Zilles, editors, Algorithmic Learning Theory, 20th International Conference, ALT 2009, Porto, Portugal, October 2009, Proceedings, volume 5809 of Lecture Notes in Artificial Intelligence, pages 338–352, Berlin/Heidelberg, 2009. Springer.

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[2994] S. Jain, F. Stephan, and T. Zeugmann. On the amount of nonconstructivity in learning formal languages from positive data. In M. Agrawal, S. B. Cooper, and A. Li, editors, Theory and Applications of Models of Computation, 9th Annual Conference, TAMC 2012, Beijing, China, May 16-21, 2012, Proceedings, volume 7287 of Lecture Notes in Computer Science, pages 423–434. Springer, 2012.

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