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| Lange and Wiehagen's Pattern Language Learning Algorithm: An Average-Case Analysis with respect to its Total Learning Time - T. Zeugmann - 1998 |
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| Language Learning from Good Examples - Steffen Lange, Jochen Nessel and Rolf Wiehagen - 1994 |
| Language Learning from Membership Queries and Characteristic Examples - Hiroshi Sakamoto - 1995 |
| Language learning from stochastic input - S. Kapur and G. Bilardi - 1992 |
| Language Learning From Texts: Degrees of Instrinsic Complexity and Their Characterizations - Sanjay Jain, Efim Kinber and Rolf Wiehagen - 2000 |
| Language Learning from Texts: Degrees of Intrinsic Complexity and Their Characterizations - Sanjay Jain, Efim Kinber and Rolf Wiehagen - 2001 |
| Language Learning from Texts: Mindchanges, Limited Memory, and Monotonicity - Efim Kinber and Frank Stephan - 1995 |
| Language learning from texts: mind changes, limited memory and monotonicity - Efim Kinber and Frank Stephan - 1995 |
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| Language learning under various types of constraint combinations - Shyam Kapur - 1994 |
| Language Learning with a Bounded Number of Mind Changes - S. Lange and T. Zeugmann - 1993 |
| Language Learning with a Neighbor System - Yasuhito Mukouchi and Masako Sato - 2000 |
| Language learning without overgeneralization - S. Kapur and G. Bilardi - 1995 |
| Language learning with some negative information - Ganesh Baliga, John Case and Sanjay Jain - 1995 |
| Language Simplification through Error-Correcting and Grammatical Inference Techniques - Juan-Carlos Amengual, Alberto Sanchis, Enrique Vidal and José-Miguel Benedi - 2001 |
| Large Margin Classification for Moving Targets - Jyrki Kivinen, Alex J. Smola and Robert C. Williamson - 2002 |
| Large Margin Classification Using the Perceptron Algorithm - Yoav Freund and Robert E. Schapire - 1999 |
| Large margin trees for induction and transduction - Donghui Wu, Kristin P. Bennett, Nello Cristianini and John Shawe-Taylor - 1999 |
| Large Scale Kernel Regression via Linear Programming - .L. Mangasarian and David R. Musicant - 2002 |
| The Last-Step Minimax Algorithm - Eiji Takimoto and Manfred K. Warmuth - 2000 |
| Latent Semantic Kernels - Nello Cristianini, John Shawe-Taylor and Huma Lodhi - 2001 |
| Layered Learning - Peter Stone and Manuela M. Veloso - 2000 |
| Lazy Bayesian rules: a lazy semi-naive Bayesian learning technique competitive to boosting decision trees - Zijian Zheng, Geoffrey I. Webb and Kai Ming Ting - 1999 |
| Lazy Induction of Descriptions for Relational Case-Based Learning - Eva Armengol and Enric Plaza - 2001 |
| Lazy Learning of Bayesian Rules - Zijian Zheng and Geoffrey I. Webb - 2000 |
| LC: A conceptual Clustering Algorithm - José Fco. Mart\'ınez-Trinidad and Guillermo Sanches-D'ıaz - 2001 |
| Leaning to optimally schedule internet banner advertisements - Naoki Abe and Atsuyoshi Nakamura - 1999 |
| Learing Horn Expressions with LogAn-H - Roni Khardon - 2000 |
| Learnability: Admissible, Co-Finite, and Hypersimple Languages - Ganesh Baliga and John Case - 1996 |
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| Learnability by fixed distributions - G. M. Benedek and A. Itai - 1988 |
| Learnability in the Presence of Classification Noise - Y. Sakakibara - November 1989 |
| Learnability of a subclass of extended pattern languages - Andrew R. Mitchell - 1998 |
| Learnability of Augmented Naive Bayes in Nominal Domains - Huajie Zhang and Charles X. Ling - 2001 |
| Learnability of Constrained Logic Programs - Saso Dzeroski, Stephen Muggleton and Stuart J. Russell - 1993 |
| Learnability of description logics - W. W. Cohen and H. Hirsh - 1992 |
| The Learnability of Description Logics with Equality Constraints - William W. Cohen and Haym Hirsh - 1994 |
| Learnability of Enumerable Classes of Recursive Functions from "Typical" Examples - Jochen Nessel - 1999 |
| The learnability of exclusive-or expansions based on monotone DNF formulas - Eiji Takimoto, Yoshifumi Sakai and Akira Maruoka - 2000 |
| The learnability of formal concepts - M. Anthony, N. Biggs and J. Shawe-Taylor - 1990 |
| Learnability of Kolmogorov-easy circuit expressions via queries - José L. Balcázar, Harry Buhrman and Montserrat Hermo - 1995 |
| Learnability of Quantified Formula - Victor Dalmau and Peter Jeavons - 1999 |
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| Learnability of Recursive, Non-determinate Theories: Some Basic Results and Techniques - M. Frazier and C. D. Page - 1993 |
| Learnability of Translations from Positive Examples - Noriko Sugimoto - 1998 |
| The learnability of unions of two rectangles in the two-dimensional discretized space - Z. Chen and F. Ameur - 1999 |
| Learnability with respect to Fixed Distributions - Gyora M. Benedek and Alon Itai - 1991 |
| Learnability with Restricted Focus of Attention Guarantees Noise-Tolerance - Shai Ben-David and Eli Dichterman - 1994 |
| LEARNABLE EVOLUTION MODEL: Evolutionary Processes Guided by Machine Learning - Ryszard S. Michalski - 2000 |
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| Learning Additive Models Online with Fast Evaluating Kernels - Mark Herbster - 2001 |
| Learning agents for uncertain environments - Stuart Russell - 1998 |
| Learning a language-independent representation for terms from a partially aligned corpus - Michael L. Littman, Fan Jiang and Greg A. Keim - 1998 |
| Learning algebraic structures from text - Frank Stephan and Yuri Ventsov - 2001 |
| Learning Algebraic Structures from Text Using Semantical Knowledge - Frank Stephan and Yuri Ventsov - 1998 |
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| A Learning Algorithm for Linear Operators - J. Mycielski - 1988 |
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| Learning and Consistency - R. Wiehagen and T. Zeugmann - 1995 |
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| Learning and Programming in Classifier Systems - Richard K. Belew and Stephanie Forrest - 1988 |
| Learning and revising theories in noisy domains - Xiaolong Zhang and Masayuki Numao - 1997 |
| Learning and robust learning of product distributions - K. Höffgen - 1993 |
| Learning and Updating of Uncertainty in Dirichlet Models - Enrique Castillo, Ali S. Hadi and Cristina Solares - 1997 |
| Learning an Intersection of a Constant Number of Halfspaces over a Uniform Distribution - Avrim Blum and Ravindran Kannan - 1997 |
| Learning an optimal decision strategy in an influence diagram with latent variables - V. G. Vovk - 1996 |
| Learning an Optimally Accurate Representation System - Russell Greiner and Dale Schuurmans - JUN 1994 |
| Learning approximately regular languages with reversible languages - Satoshi Kobayashi and Takashi Yokomori - 1997 |
| Learning a Probability Distribution Efficiently and Reliably - P. Laird and E. Gamble - October 1988 |
| Learning a representation for optimizable formulas - Hans Kleine Büning and Theodor Lettmann - 1996 |
| Learning arithmetic read-once formulas - N. H. Bshouty, T. R. Hancock and L. Hellerstein - 1992 |
| Learning Arm Kinematics and Dynamics - C. G. Atkeson - 1989 |
| Learning a subclass of context-free languages - J. D. Emerald, K. G. Subramanian and D. G. Thomas - 1998 |
| Learning a subclass of linear languages from positive structural information - José M. Sempere and G. Nagaraja - 1998 |
| Learning atomic formulas with prescribed properties - Irene Tsapara and György Turán - 1998 |
| Learning at the Knowledge Level - Thomas G. Dietterich - 1986 |
| Learning Automata - An Introduction - K. S. Narendra and M. A. L. Thathachar - 1989 |
| Learning Automata - A Survey - K. S. Narendra and M. A. L. Thathachar - 1974 |
| Learning Automata from Ordered Examples - Sara Porat and Jerome A. Feldman - 1991 |
| Learning Bayesian Belief Networks Based on the MDL Principle: An Efficient Algorithm Using the Branch and Bound Technique - Joe Suzuki - 1999 |
| Learning Bayesian belief networks based on the minimum description length principle: an efficient algorithm using the B \& B technique - Joe Suzuki - 1996 |
| Learning Bayesian Belief Networks Based on the Minimum Description Length Principle: Basic Properties - Joe Suzuki - 1999 |
| Learning Bayesian Networks for Diverse and Varying Numbers of Evidence Sets - Zu Whan Kim and Ramakant Nevatia - 2000 |
| Learning Bayesian networks: the combination of knowledge and statistical data - David Heckerman, Dan Geiger and David M. Chickering - 1995 |
| Learning Behaviors of Automata from Multiplicity and Equivalence Queries - Francesco Bergadano and Stefano Varricchio - 1996 |
| Learning behaviors of automata from shortest counterexamples - F. Bergadano and S. Varricchio - 1995 |
| Learning belief networks in the presence of missing values and hidden variables - Nir Friedman - 1997 |
| Learning binary perceptrons perfectly efficiently - Shao C. Fang and Santosh S. Venkatesh - 1996 |
| Learning binary relations and total orders - S. A. Goldman, R. L. Rivest and R. E. Schapire - October 1993 |
| Learning Binary Relations, Total Orders, and Read-Once Formulas - S. Goldman - September 1990 |
| Learning binary relations using weighted majority voting - Sally A. Goldman and Manfred K. Warmuth - 1995 |
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| Learning Boolean formulas - Michael Kearns, Ming Li and Leslie Valiant - 1994 |
| Learning Boolean Functions in an Infinite Attribute Space - A. Blum - October 1992 |
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| Learning Boxes in High Dimension - Amos Beimel and Eyal Kushilevitz - 1998 |
| Learning branches and learning to win closed games - Martin Kummer and Matthias Ott - 1996 |
| Learning by a population of perceptrons - Kukjin Kang and Jong-Hoon Oh - 1995 |
| Learning by Distances - S. Ben-David, A. Itai and E. Kushilevitz - 1995 |
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| Learning by experimentation: incremental refinement of incomplete planning domains - Yolanda Gil - 1994 |
| Learning by extended statistical queries and its relation to PAC learning - Eli Shamir and Clara Schwartzman - 1995 |
| Learning by Failing to Explain: Using Partial Explanations to Learn in Incomplete or Intractable Domains - Robert J. Hall - 1988 |
| Learning by Making Models - P. Laird - 1988 |
| Learning by observation and practice: an incremental approach for planning operator acquisition - Xuemei Wang - 1995 |
| Learning by smoothing: a morphological approach - W. M. Kim - 1991 |
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| Learning Causal Patterns: Making a Transition from Data-Driven to Theory-Driven Learning - Michael Pazzani - 1993 |
| Learning changing concepts by exploiting the structure of change - Peter L. Bartlett, Shai Ben-David and Sanjeev R. Kulkarni - 1996 |
| Learning Changing Concepts by Exploiting the Structure of Change - Peter L. Bartlett, Shai Ben-David and Sanjeev R. Kulkarni - 2000 |
| Learning Chomsky-like Grammars for Biological Sequence Families - S. H. Muggleton, C. H. Bryant and A. Srinivasan - 2000 |
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| Learning Classification Programs: The Genetic Algorithm Approach - Attilio Giordana and Giuseppe Lo Bello - 1998 |
| Learning code regular and code linear languages - J. D. Emerald, K. G. Subramanian and D. G. Thomas - 1996 |
| Learning Coherent Concepts - Ashutosh Garg and Dan Roth - 2001 |
| Learning collaborative information filters - Daniel Billsus and Michael J. Pazzani - 1998 |
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| Learning Commutative Deterministic Finite State Automata in Polynomial Time - N. Abe - 1991 |
| The learning complexity of smooth functions of a single variable - D. Kimber and P. Long - 1992 |
| Learning complicated concepts reliably and usefully - R. L. Rivest and R. Sloan - 1988 |
| Learning comprehensible descriptions of multivariate time series - Mohammed Waleed Kadous - 1999 |
| Learning Concatenations of Locally Testable Languages from Positive Data - Satoshi Kobayashi and Takashi Yokomori - 1994 |
| Learning Concepts by Asking Questions - C. Sammut and R. Banerji - 1986 |
| Learning Concepts from Sensor Data of a Mobile Robot - Volker Klingspor, Katharina J. Morik and Anke D. Rieger - 1996 |
| Learning conjunctions of Horn clauses - D. Angluin, M. Frazier and L. Pitt - 1992 |
| Learning conjunctions of two unate DNF formulas: computational and informational results - Aaron Feigelson and Lisa Hellerstein - 1996 |
| Learning Conjunctive Concepts in Structural Domains - D. Haussler - 1989 |
| Learning Context-Free Grammars from Partially Structured Examples - Yasubumi Sakakibara and Hidenori Muramatsu - 2000 |
| Learning context-free grammars from structural data in polynomial time - Yasubumi Sakakibara - 1990 |
| Learning Context-Free Grammars with a Simplicity Bias - Pat Langley and Sean Stromsten - 2000 |
| Learning context to disambiguate word senses - Ellen M. Voorhees, Claudia Leacock and Geoffrey Towell - 1995 |
| Learning Controllers for Industrial Robots - C. Baroglio, A. Giordana, M. Kaiser, M. Nuttin and R. Piola - 1996 |
| Learning Coordination Strategies for Cooperative Multiagent Systems - F. Ho and M. Kamel - 1998 |
| Learning counting functions with queries - Zhixiang Chen and Steven Homer - 1997 |
| A Learning Criterion for Stochastic Rules - Kenji Yamanishi - 1992 |
| Learning curve bounds for a Markov decision process with undiscounted rewards - Lawrence K. Saul and Satinder P. Singh - 1996 |
| Learning Curved Multinomial Subfamilies for Natural Language Processing and Information Retrieval - Keith Hall and Thomas Hofmann - 2000 |
| Learning curves in large neural networks - H. Sompolinsky, H. S. Seung and N. Tishby - 1991 |
| Learning Decision Lists - Ronald L. Rivest - 1987 |
| Learning decision lists and trees with equivalence-queries - Hans Ulrich Simon - 1995 |
| Learning Decision Trees from Random Examples - A. Ehrenfeucht and D. Haussler - 1989 |
| Learning Decision Trees using the Fourier Spectrum - E. Kushilevitz and Y. Mansour - 1993 |
| Learning Declarative Control Rules for Constraint-Based Planning - Yi-Cheng Huang, Bart Selman and Henry Kautz - 2000 |
| Learning Default Concepts - Dale Schuurmans and Russell Greiner - 1994 |
| Learning despite concept variation by finding structure in attribute-based data - Eduardo Pérez and Larry A. Rendell - 1996 |
| Learning deterministic even linear languages from positive examples - Takeshi Koshiba, Erkki Mäkinen and Yuji Takada - 1997 |
| Learning deterministic finite automaton with a recurrent neural network - Laura Firoiu, Tim Oates and Paul R. Cohen - 1998 |
| Learning determnistic regular grammars from stochastic samples in polynomial time - Rafael C. Carrasco and Jose Oncina - 1999 |
| Learning DFA from simple examples - Rajesh Parekh and Vasant Honavar - 1997 |
| Learning DFA from Simple Examples - Rajesh Parekh and Vasant Honavar - 2001 |
| Learning discriminatory and descriptive rules by an inductive logic programming system - Maziar Palhang and Arcot Sowmya - 1999 |
| Learning Disjunctions of Conjunctions - L. G. Valiant - 1985 |
| Learning disjunctions of features - Stephen Kwek - 1997 |
| Learning disjunctive concepts by means of genetic algorithms - Attilio Giordana, Lorenza Saitta and Floriano Zini - 1994 |
| Learning disjunctive concepts using domain knowledge - Harish Ragavan and Larry Rendell - 1994 |
| Learning Distributed Representations by Mapping Concepts and Relations into a Linear Space - Alberto Paccanaro and Geoffrey E. Hinton - 2000 |
| Learning Distributed Representations of Concepts - G. E. Hinton - 1986 |
| Learning Distributions by Their Density Levels: A Paradigm for Learning without a Teacher - Shai Ben-David and Michael Lindenbaum - 1997 |
| Learning Distributions from Random Walks - Funda Ergün, S. Ravi Kumar and Ronitt Rubinfeld - 1997 |
| Learning DNF formulae under classes of probability distributions - M. Flammini, A. Marchetti-Spaccamela and L. K. Cera - 1992 |
| Learning DNF over the Uniform Distribution Using a Quantum Example Oracle - Nader H. Bshouty and Jeffrey C. Jackson - 1999 |
| Learning DNF under the uniform distribution in quasi-polynomial time - K. Verbeurgt - 1990 |
| Learning Domain Theories using Abstract Beckground Knowledge - Peter Clark and Stan Matwin - 1993 |
| Learning effect of a dynamic thesaurus in associated information retrieval - H. Kimoto and T. Iwadera - 1992 |
| Learning Elementary Formal Systems - Setsuo Arikawa, Takeshi Shinohara and Akihiro Yamamoto - 1992 |
| Learning Embedded Maps of Markov Processes - Yaakov Engel and Shie Mannor - 2001 |
| Learning Erasing Pattern Languages with Queries - Jochen Nessel and Steffen Lange - 2000 |
| Learning evaluation functions for large acyclic domains - Justin A. Boyan and Andrew W. Moore - 1996 |
| Learning Expressions over Monoids - Ricard Gavaldà and Denis Thérien - 2001 |
| Learning Fallible Deterministic Finite Automata - Dana Ron and Ronitt Rubinfeld - 1995 |
| Learning Faster than Promised by the Vapnik-Chervonenkis Dimension - A. Blumer and N. Littlestone - 1989 |
| Learning Filaments - Geoffrey J. Gordon and Andrew Moore - 2000 |
| Learning finite automata using local distinguishing experiments - Wei-Min Shen - 1995 |
| Learning first-order acyclic Horn programs from entailment - Chandra Reddy and Prasad Tadepalli - 1998 |
| Learning first order universal Horn expressions - Roni Khardon - 1998 |
| Learning Fixed-Dimension Linear Thresholds from Fragmented Data - Paul W. Goldberg - November 2001 |
| Learning fixed-dimension linear thresholds from fragmented data - Paul W. Goldberg - 1999 |
| Learning fixed point patterns by recurrent networks - Leong Kwan Li - 1994 |
| Learning Formal Languages Based on Control Sets - Yuji Takada - 1995 |
| Learning formulae from elementary facts - Jānis Bārzdiņs, Rīsiņs Freivalds and Carl H. Smith - 1997 |
| Learning from a consistently ignorant teacher - Michael Frazier, Sally Goldman, Nina Mishra and Leonard Pitt - 1996 |
| Learning from a consistently ignorant teacher - M. Frazier, S. Goldman, N. Mishra and L. Pitt - 1994 |
| Learning from a mixture of labeled and unlabeled examples with parametric side information - Joel Ratsaby and Santosh S. Venkatesh - 1995 |
| Learning from a population of hypotheses - Michael Kearns and H. Sebastian Seung - 1995 |
| Learning from Approximate Data - Shirley Cheung - 2000 |
| Learning from data with bounded inconsistency: theoretical and experimental results - Haym Hirsh and William W. Cohen - 1994 |
| Learning from Delayed Rewards - C. J. C. H. Watkins - May 1989 |
| Learning from entailment: An application to propositional Horn sentences - Michael Frazier and Leonard Pitt - June 1993 |
| Learning from Entailment of Logic Programs with Local Variables - M. R. K. Krishna Rao and A. Sattar - 1998 |
| Learning from Examples and Membership Queries with Structured Determinations - Prasad Tadepalli and Stuart Russell - 1998 |
| Learning from Examples in a Single-Layer Neural Network - D. Hansel and H. Sompolinsky - 1990 |
| Learning from Examples in Large Neural Networks - H. Sompolinsky, N. Tishby and H. S. Seung - 1990 |
| Learning from Examples with Typed Equational Programming - Akira Ishino and Akihiro Yamamoto - 1994 |
| Learning From Examples With Unspecified Attribute Values - Sally A. Goldman, Stephen S. Kwek and Stephen D. Scott - 1997 |
| Learning from Expert Hypotheses and Training Examples - Shigeo Kaneda, Hussein Almuallim, Yasuhiro Akiba and Megumi Ishi - 1998 |
| Learning from Good and Bad Data - Philip D. Laird - 1988 |
| Learning from good examples - R. Freivalds, E. B. Kinber and R. Wiehagen - 1995 |
| Learning from incomplete boundary queries using split graphs and hypergraphs - Robert H. Sloan and György Turán - 1997 |
| Learning from Labeled and Unlabeled Data Using Graph Mincuts - Avrim Blum and Shuchi Chawla - 2001 |
| Learning from Multiple Sources of Inaccurate Data - Ganesh Baliga, Sanjay Jain and Arun Sharma - 1997 |
| Learning from Multiple Sources of Inaccurate Data - G. Baliga, S. Jain and A. Sharma - 1992 |
| Learning from noisy examples - D. Angluin and P. Laird - 1988 |
| Learning from Positive and Unlabeled Examples - Fabien Letouzey, François Denis and Rémi Gilleron - 2000 |
| Learning from positive-only examples - R. Berwick - 1986 |
| Learning from Random Text - Peter Rossmanith - 1999 |
| Learning Function-Free Horn Expressions - Roni Khardon - 1999 |
| Learning Functions from Examples - B. K. Natarajan - 1987 |
| Learning functions of k terms - A. Blum and M. Singh - 1990 |
| Learning functions represented as multiplicity automata - Amos Beimel, Francesco Bergadano, Nader H. Bshouty, Eyal Kushilevitz and Stefano Varricchio - 2000 |
| Learning fuzzy decision trees - Bruno Apolloni, Giacomo Zamponi and Anna Maria Zanaboni - 1998 |
| A Learning Generalization Bound with an Application to Sparse-Representation Classifiers - Yoram Gat - 2001 |
| Learning goal-decomposition rules using exercises - Chandra Reddy and Prasad Tadepalli - 1997 |
| Learning goal oriented Bayesian networks for telecommunications risk management - Kazuo J. Ezawa, Moninder Singh and Steven W. Norton - 1996 |
| Learning grammatical stucture using statistical decision-trees - David M. Magerman - 1996 |
| Learning hard concepts through constructive induction: framework and rationale - Larry Rendell and Raj Seshu - 1994 |
| Learning heirarchical rule sets - J. Kivinen, H. Mannila and E. Ukkonen - 1992 |
| Learning hierarchical performance knowledge by observation - Michael van Lent and John Laird - 1999 |
| Learning hierarchies from ambiguous natural language data - Takefumi Yamazaki, Michael J. Pazzani and Christopher Merz - 1995 |
| Learning How to Separate - Sanjay Jain and Frank Stephan - 2001 |
| Learning mu-branching programs with queries - V. Raghavan and D. Wilkins - 1993 |
| Learning in abstraction space - George Drastal - 1994 |
| Learning in a Layered Network with many Fixed-Function Hidden Nodes - N. Littlestone - June 1987 |
| Learning in artificial neural networks: a statistical perspective - H. White - 1990 |
| Learning in Case-Based Classification Algorithms - Christoph Globig and Stefan Wess - 1995 |
| Learning Information Extraction Rules for Semi-Structured and Free Text - Stephen Soderland - 1999 |
| Learning in multi-agent environments - P. Brazdil - 1992 |
| Learning in neural networks - S. Judd - 1988 |
| Learning in Non-stationary Conditions: A Control Theoretic Approach - Jefferson Coelho and Rod Grupen - 2000 |
| Learning in parallel - J. Vitter and J. Lin - 1992 |
| Learning in Pattern Recognition - T. M. Cover - 1969 |
| Learning in permutation groups (extended abstract) - U. Feige and A. Shamir - 1987 |
| Learning Integer Lattices - D. Helmbold, R. Sloan and M. K. Warmuth - 1992 |
| Learning Intermediate Concepts - Stephen S. Kwek - 2001 |
| Learning internal representations - Jonathan Baxter - 1995 |
| Learning Internal Representations by Error Propagation - D. E. Rumelhart, G. E. Hinton and R. J. Williams - 1986 |
| Learning in the Presence of Additional Information and Inaccurate Information - S. Jain - 1990 |
| Learning in the Presence of Concept Drift and Hidden Contexts - Gerhard Widmer and Miroslav Kubat - 1996 |
| Learning in the presence of finitely or infinitely many irrelevant attributes - Avrim Blum, Lisa Hellerstein and Nick Littlestone - 1995 |
| Learning in the Presence of Inaccurate Information - Mark Fulk and Sanjay Jain - 1996 |
| Learning in the Presence of Inaccurate Information - M. A. Fulk and S. Jain - August 1989 |
| Learning in the presence of malicious errors - M. Kearns and M. Li - 1993 |
| Learning in the Presence of Partial Explanations - S. Jain and A. Sharma - 1991 |
| Learning in the 'real world' - Lorenzo Saitta and Filippo Neri - 1998 |
| Learning in threshold networks - P. Raghavan - 1988 |
| Learning k-Bounded Context-Free Grammars - D. Angluin - August 1987 |
| Learning k-DNF with Noise in the Attributes - G. Shackelford and D. Volper - 1988 |
| Learning k mu decision trees on the uniform distribution - T. Hancock - 1993 |
| Learning k-piecewise testable languages from positive data - José Ruiz and Pedro Garcia - 1996 |
| Learning k-term DNF Formulas using Queries and Counterexamples - D. Angluin - August 1987 |
| Learning k-term DNF formulas with an incomplete membership oracle - S. A. Goldman and H. D. Mathias - 1992 |
| Learning k-term monotone Boolean formulae - Yoshifumi Sakai and Akira Maruoka - 1993 |
| Learning k-Variable Pattern Languages Efficiently Stochastically Finite on Average from Positive Data - Peter Rossmanith and Thomas Zeugmann - 1998 |
| Learning languages and functions by erasing - Sanjay Jain, Efim Kinber, Steffen Lange, Rolf Wiehagen and Thomas Zeugmann - 2000 |
| Learning Languages by Collecting Cases and Tuning Parameters - Yasubumi Sakakibara, Klaus P. Jantke and Steffen Lange - 1994 |
| Learning Languages in a Union - Sanjay Jain, Yen Kaow Ng and Tiong Seng Tay - 2001 |
| Learning linear grammars from structural information - Jose M. Sempere and Antonio Fos - 1996 |
| Learning linear threshold functions in the presence of classification noise - T. Bylander - 1994 |
| Learning Local and Recognizable omega-languages and Monadic Logic Programs - A. Saoudi - 1994 |
| Learning Logical Definitions from Relations - J. R. Quinlan - 1990 |
| Learning, Logic, and Topology in a Common Framework - Eric Martin, Arun Sharma and Frank Stephan - 2002 |
| Learning Logic Programs by using the Product Homomorphism Method - Tamás Horváth, Robert H. Sloan and György Turán - 1997 |
| Learning Machines - J. Case - 1986 |
| Learning Machines - N. J. Nilsson - 1965 |
| Learning Markov chains with variable length memory from noisy output - Dana Angluin and Miklós Csűrös - 1997 |
| Learning Matrix Functions over Rings - Nader H. Bshouty, Christino Tamon and David K. Wilson - 1998 |
| Learning Minimal Covers of Functional Dependencies with Queries - Montserrat Hermo and Vitor Lavin - 1999 |
| A learning model for oscillatory networks - Jun Nishii - 1998 |
| Learning Monotone DNF From a Teacher That Almost Does Not Answer Membership Queries - Nader H. Bshouty and Nadav Eiron - 2001 |
| Learning monotone DNF with an incomplete membership oracle - D. Angluin and D. K. Slonim - 1991 |
| Learning monotone k mu-DNF formulas on product distributions - T. Hancock and Y. Mansour - 1991 |
| Learning monotone log-term DNF formulas - Y. Sakai and A. Maruoka - 1994 |
| Learning Monotone Log-Term DNF Formulas under the Uniform Distribution - Y. Sakai and A. Maruoka - 2000 |
| Learning monotone term decision lists - David Guijarro, Victor Lavin and Vijay Raghavan - 1997 |
| Learning Multiple Models for Reward Maximization - Dani Goldberg and Maja J. Matarić - 2000 |
| Learning Multiplicity Automata from Smallest Counterexamples - Jürgen Forster - 1999 |
| Learning nearly monotone k-term DNF - Jorge Castro, David Guijarro and Victor Lavin - 1997 |
| Learning nested differences in the presence of malicious noise - Peter Auer - 1997 |
| Learning Nested Differences of Intersection Closed Concept Classes - David Helmbold, Robert Sloan and Manfred K. Warmuth - 1990 |
| Learning nested differences of intersection-closed concept classes - D. Helmbold, R. Sloan and M. K. Warmuth - 1989 |
| Learning New Principles From Precedents and Exercises: The Details - P. H. Winston - May 1981 |
| Learning noisy perceptrons by a perceptron in polynomial time - Edith Cohen - 1997 |
| Learning non-deterministic finite automata from queries and counterexamples - Takashi Yokimori - 1994 |
| Learning nonoverlapping perceptron networks from examples and membership queries - Thomas R. Hancock, Mostefa Golea and Mario Marchand - 1994 |
| Learning non-parametric densities by finite-dimensional parametric hypotheses - K. Yamanishi - 1992 |
| Learning Non-parametric Smooth Rules by Stochastic Rules with Finite Partitioning - K. Yamanishi - 1994 |
| Learning of Associative Memory Networks Based upon Cone-Like Domains of Attraction - Koichi Niijima - 1997 |
| Learning of Boolean Functions Using Support Vector Machines - Ken Sadohara - 2001 |
| Learning of context-sensitive language acceptors through regular inference and constrained induction - René Alquézar, Alberto Sanfeliu and Jordi Cueva - 1996 |
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| Learning ordered binary decision diagrams - Ricard Gavaldà and David Guijarro - 1995 |
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