Automatic Learning from Positive Data and Negative Counterexamples

[1]  Ryo Yoshinaka,et al.  Distributional learning of parallel multiple context-free grammars , 2013, Machine Learning.

[2]  John Case,et al.  Automatic functions, linear time and learning , 2013, Log. Methods Comput. Sci..

[3]  Samuel E. Moelius Characteristics of Minimal Effective Programming Systems , 2012, CiE.

[4]  Arno Pauly,et al.  Closed choice and a Uniform Low Basis Theorem , 2010, Ann. Pure Appl. Log..

[5]  Sanjay Jain,et al.  ON AUTOMATIC FAMILIES , 2011 .

[6]  Sumit Gulwani,et al.  Synthesis of loop-free programs , 2011, PLDI '11.

[7]  Alexander Clark Towards General Algorithms for Grammatical Inference , 2010, ALT.

[8]  Sanjay Jain,et al.  Learnability of Automatic Classes , 2010, LATA.

[9]  John Case,et al.  Difficulties in Forcing Fairness of Polynomial Time Inductive Inference , 2009, ALT.

[10]  Satoru Miyano,et al.  A machine discovery from amino acid sequences by decision trees over regular patterns , 1993, New Generation Computing.

[11]  Klaus P. Jantke Monotonic and non-monotonic inductive inference , 2009, New Generation Computing.

[12]  Sanjay Jain,et al.  Iterative Learning from Positive Data and Negative Counterexamples , 2007, ALT.

[13]  Sandra Zilles,et al.  Relations between Gold-style learning and query learning , 2005, Inf. Comput..

[14]  Sanjay Jain,et al.  Learning Languages from Positive Data and Negative Counterexamples , 2004, ALT.

[15]  Sandra Zilles,et al.  Comparison of Query Learning and Gold-Style Learning in Dependence of the Hypothesis Space , 2004, ALT.

[16]  Rolf Wiehagen,et al.  Learning recursive languages from good examples , 2004, Annals of Mathematics and Artificial Intelligence.

[17]  Henning Fernau,et al.  Even linear simple matrix languages: formal language properties and grammatical inference , 2002, Theor. Comput. Sci..

[18]  Susumu Hayashi,et al.  Limit-Computable Mathematics and Its Applications , 2002, CSL.

[19]  Robert H. Sloan,et al.  BOOK REVIEW: "SYSTEMS THAT LEARN: AN INTRODUCTION TO LEARNING THEORY, SECOND EDITION", SANJAY JAIN, DANIEL OSHERSON, JAMES S. ROYER and ARUN SHARMA , 2001 .

[20]  Jochen Nessel,et al.  Learning erasing pattern languages with queries , 2005, Theor. Comput. Sci..

[21]  Achim Blumensath,et al.  Automatic structures , 2000, Proceedings Fifteenth Annual IEEE Symposium on Logic in Computer Science (Cat. No.99CB36332).

[22]  Thomas Zeugmann,et al.  Incremental Learning from Positive Data , 1996, J. Comput. Syst. Sci..

[23]  Frank Stephan,et al.  Language Learning from Texts: Mindchanges, Limited Memory, and Monotonicity , 1995, Inf. Comput..

[24]  Carl H. Smith,et al.  On the impact of forgetting on learning machines , 1995, JACM.

[25]  Thomas Zeugmann,et al.  A Guided Tour Across the Boundaries of Learning Recursive Languages , 1995, GOSLER Final Report.

[26]  Anil Nerode,et al.  Automatic Presentations of Structures , 1994, LCC.

[27]  Takeshi Shinohara,et al.  Rich Classes Inferable from Positive Data: Length-Bounded Elementary Formal Systems , 1994, Inf. Comput..

[28]  Thomas Zeugmann,et al.  Language learning in dependence on the space of hypotheses , 1993, COLT '93.

[29]  John Case,et al.  Language Learning with Some Negative Information , 1993, J. Comput. Syst. Sci..

[30]  Akihiro Yamamoto,et al.  Algorithmic Learning Theory with Elementary Formal Systems , 1992 .

[31]  Akihiro Yamamoto,et al.  Learning Elementary Formal Systems , 1992, Theor. Comput. Sci..

[32]  Satoru Miyano,et al.  More About Learning Elementary Formal Systems , 1991, Nonmonotonic and Inductive Logic.

[33]  Peter H. Schmitt,et al.  Nonmonotonic and Inductive Logic: 1st International Workshop Karlsruhe, Germany, December 4-7, 1990 Proceedings , 1991 .

[34]  Tatsuya Motoki,et al.  Inductive Inference from all Positive and Some Negative Data , 1991, Inf. Process. Lett..

[35]  Rolf Wiehagen A Thesis in Inductive Inference , 1990, Nonmonotonic and Inductive Logic.

[36]  Daniel N. Osherson,et al.  Systems That Learn: An Introduction to Learning Theory for Cognitive and Computer Scientists , 1990 .

[37]  Mark A. Fulk Prudence and Other Conditions on Formal Language Learning , 1990, Inf. Comput..

[38]  Leonard Pitt,et al.  Inductive Inference, DFAs, and Computational Complexity , 1989, AII.

[39]  Tao Jiang,et al.  Learning regular languages from counterexamples , 1988, COLT '88.

[40]  Carl H. Smith,et al.  Learning via queries , 1988, [Proceedings 1988] 29th Annual Symposium on Foundations of Computer Science.

[41]  Dana Angluin,et al.  Queries and concept learning , 1988, Machine Learning.

[42]  R. Treiman,et al.  Brown & Hanlon revisited: mothers' sensitivity to ungrammatical forms , 1984, Journal of Child Language.

[43]  John Case,et al.  Comparison of Identification Criteria for Machine Inductive Inference , 1983, Theor. Comput. Sci..

[44]  John Case,et al.  Machine Inductive Inference and Language Identification , 1982, ICALP.

[45]  M. Bowerman Starting to talk worse: Clues to language acquisition from children's late speech errors , 1982 .

[46]  Dana Angluin,et al.  Finding Patterns Common to a Set of Strings , 1980, J. Comput. Syst. Sci..

[47]  Dana Angluin,et al.  Inductive Inference of Formal Languages from Positive Data , 1980, Inf. Control..

[48]  S. Pinker Formal models of language learning , 1979, Cognition.

[49]  Manuel Blum,et al.  Toward a Mathematical Theory of Inductive Inference , 1975, Inf. Control..

[50]  Rolf Wiehagen Limes-Erkennung rekursiver Funktionen durch spezielle Strategien , 1975, J. Inf. Process. Cybern..

[51]  Jr. Hartley Rogers Theory of Recursive Functions and Effective Computability , 1969 .

[52]  E. Mark Gold,et al.  Language Identification in the Limit , 1967, Inf. Control..

[53]  M. Kendall,et al.  The Logic of Scientific Discovery. , 1959 .