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1994open this document and view contents On Learning Simple Deterministic and Probabilistic Neural Concepts - M. Golea and M. Marchand
open this document and view contents Using Experts for Predicting Continuous Outcomes - J. Kivinen and M. Warmuth
open this document and view contents Valid Generalisation of Functions from Close Approximations on a Sample - M. Anthony and J. Shawe-Taylor
open this document and view contents The strength of noninclusions for teams of finite learners - M. Kummer
open this document and view contents Associative methods in reinforcement learning: an empirical study - Leslie Pack Kaelbling
open this document and view contents The Power of Self-Directed Learning - S. A. Goldman and R. H. Sloan
open this document and view contents On the Complexity of Learning on Neural Nets - W. Maass
open this document and view contents An efficient subsumption algorithm for inductive logic programming - Jörg-Uwe Kietz and Marcus Lübbe
open this document and view contents Hard questions about easy tasks: issues from learning to play games - Susan L. Epstein
open this document and view contents Approximate methods for sequential decision making using expert advice - T. H. Chung
open this document and view contents Predicting {0,1} Functions on Randomly Drawn Points - D. Haussler, N. Littlestone and M. K. Warmuth
open this document and view contents Rule induction for semantic query optimization - Chun-Nan Hsu and Craig A. Knoblock
open this document and view contents Classification of Predicates and Languages - R. Wiehagen, C. H. Smith and T. Zeugmann
open this document and view contents Simple Translation-Invariant Concepts Are Hard to Learn - M. Jerrum
open this document and view contents Open problems in Systems that learn - Mark Fulk, Sanjay Jain and Daniel N. Osherson
open this document and view contents Bounds on the sample complexity of Bayesian learning using information theory and the VC dimension - David Haussler, Michael Kearns and Robert E. Schapire
open this document and view contents Generalizing version spaces - Haym Hirsh
open this document and view contents Choosing a learning team: a topological approach - K. Aps\=ıtis, R. Freivalds and C. Smith
open this document and view contents On-line learning of rectangles and unions of rectangles - Zhixiang Chen and Wolfgang Maass
open this document and view contents Efficient agnostic PAC-learning with simple hypotheses - W. Maass
open this document and view contents Enumerable Classes of Total Recursive Functions: Complexity of Inductive Inference - Andris Ambainis and Juris Smotrovs
open this document and view contents Quantifying Prior Determination Knowledge Using the PAC Learning Model - Sridhar Mahadevan and Prasad Tadepalli
open this document and view contents Read-twice DNF Formulas are Properly Learnable - K. Pillaipakkamnatt and V. Raghavan
open this document and view contents Complexity-based induction - Darrell Conklin and Ian H. Witten
open this document and view contents Boosting and other machine learning algorithms - Harris Drucker, Corinna Cortes, L. D. Jackel, Yann LeCun and Vladimir Vapnik
open this document and view contents Neural network modeling of physiological processes - Volker Tresp, John Moody and Wolf-Rüdiger Delong
open this document and view contents Cryptographic limitations on learning Boolean formulae and finite automata - Michael Kearns and Leslie Valiant
open this document and view contents Identifying Regular Languages over Partially-Commutative Monoids - Claudio Ferretti and Giancarlo Mauri
open this document and view contents Modeling Cognitive Development on Balance Scale Phenomena - Thomas R. Schultz, Denis Mareschal and William C. Schmidt
open this document and view contents A Theory for Memory-Based Learning - Jyh-Han Lin and Jeffrey Scott Vitter
open this document and view contents Guest Editor's Introduction - Lisa Hellerstein
open this document and view contents Learning non-deterministic finite automata from queries and counterexamples - Takashi Yokimori
open this document and view contents Getting the most from flawed theories - Moshe Koppel, Alberto Maria Segre and Ronen Feldman
open this document and view contents Neural Network-Based Vision for Precise Control of a Walking Robot - Dean A. Pomerleau
open this document and view contents Learning probabilistic automata with variable memory length - D. Ron, Y. Singer and N. Tishby
open this document and view contents Machine learning and qualitative reasoning - Ivan Bratko
open this document and view contents Reward functions for accelerated learning - Maja J. Mataric
open this document and view contents Learning Probabilistic Read-once Formulas on Product Distributions - Robert E. Schapire
open this document and view contents Reducing misclassification costs - Michael Pazzani, Christopher Merz, Patrick Murphy, Kamal Ali, Timothy Hume and Clifford Brunk
open this document and view contents Toward efficient agnostic learning - Michael J. Kearns, Robert E. Schapire and Linda M. Sellie
open this document and view contents From Specifications to Programs: Induction in the Service of Synthesis - Nachum Dershowitz
open this document and view contents Learning with queries but incomplete information - R. H. Sloan and G. Turán
open this document and view contents Learning monotone log-term DNF formulas - Y. Sakai and A. Maruoka
open this document and view contents Statistical Methods for Analyzing Speedup Learning Experiments - Oren Etzioni and Ruth Etzioni
open this document and view contents Machine Discovery in the Presence of Incomplete or Ambiguous Data - S. Lange and P. Watson
open this document and view contents Explanation-Based Reuse of Prolog Programs - Yasuyuki Koga, Eiju Hirowatari and Setsuo Arikawa
open this document and view contents How fast can a threshold gate learn? - Wolgang Maass and György Turán
open this document and view contents A statistical approach to decision tree modeling - M. I. Jordan
open this document and view contents Evolution of a subsumption architecture that performs a wall following task for an autonomous mobile robot - John R. Koza
open this document and view contents Contrastive learning with graded random networks - Javier R. Movellan and James L. McClelland
open this document and view contents Efficient distribution-free learning of probabilistic concepts - Michael J. Kearns and Robert E. Schapire
open this document and view contents Sensitivity constraints in learning - Scott H. Clearwater and Yongwon Lee
open this document and view contents Inclusion problems in parallel learning and games - M. Kummer and F. Stephan
open this document and view contents On Learning Monotone DNF Formulae under Uniform Distributions - L. Kucera, A. Marchettispaccamela and M. Protasi
open this document and view contents A Neuroidal Model for Cognitive Functions - L. Valiant
open this document and view contents The power of team exploration: two robots can learn unlabeled directed graphs - Michael A. Bender and Donna K. Slonim
open this document and view contents Inducing probabilistic grammars by Byasian model merging - A. Stolcke and S. Omohundro
open this document and view contents Small sample decision tree pruning - Sholom M. Weiss and Nitin Indurkhya
open this document and view contents A Calculus for Logical Clustering - Shuo Bai
open this document and view contents Filter likelihoods and exhaustive learning - David H. Wolpert
open this document and view contents Using Kullback-Leibler Divergence in Learning Theory - S. Anoulova and S. Pölt
open this document and view contents A Unified Approach to Inductive Logic and Case-Based Reasoning - Michael M. Richter
open this document and view contents The effect of adding relevance information in a relevance feedback environment - C. Buckley, G. Salton and J. Allan
open this document and view contents Improving accuracy of incorrect domain theories - L. Asker
open this document and view contents Incremental reduced error pruning - Johannes Fürnkranz and Gerhard Widmer
open this document and view contents Defining the limits of analogical planning - Diane J. Cook
open this document and view contents Learning stochastic regular grammars by means of a state merging method - R. Carrasco and J. Oncina
open this document and view contents Predicate invention and utilization - S. Muggleton
open this document and view contents Therapy Plan Generation as Program Synthesis - Oksana Arnold and Klaus P. Jantke
open this document and view contents Constructive Induction for Recursive Programs - Chowdhury Rahman Mofizur and Masayuki Numao
open this document and view contents Language learning under various types of constraint combinations - Shyam Kapur
open this document and view contents Learning by experimentation: incremental refinement of incomplete planning domains - Yolanda Gil
open this document and view contents Fat-shattering and the learnability of real-valued functions - P. L. Bartlett, P. M. Long and R. C. Williamson
open this document and view contents A comparitive study of the Kohonen self-organizing map and the elastic net - Yiu-fai Wong
open this document and view contents On the intrinsic complexity of language identification - S. Jain and A. Sharma
open this document and view contents Hierarchical self-organization in genetic programming - Justinian P. Rosca and Dana H. Ballard
open this document and view contents Induction Inference of an Approximate Concept from Positive Data - Yasuhito Mukouchi
open this document and view contents Minimal Samples of Positive Examples Identifying k-CNF Boolean Functions - A. T. Ogielski
open this document and view contents Hamiltonian dynamics of neural networks - Ulrich Ramacher
open this document and view contents Heterogeneous uncertainty sampling for supervised learning - David D. Lewis and Jason Catlett
open this document and view contents Experiments on the transfer of knowledge between neural networks - Lorien Y. Pratt
open this document and view contents Learning Languages by Collecting Cases and Tuning Parameters - Yasubumi Sakakibara, Klaus P. Jantke and Steffen Lange
open this document and view contents A new method for predicting protein secondary structures based on stochastic tree grammars - Naoki Abe and Hiroshi Mamitsuka
open this document and view contents Algorithms and Lower Bounds for On-Line Learning of Geometrical Concepts - Wolfgang Maass and György Turán
open this document and view contents Simulating Access to hidden information while learning - P. Auer and P. Long
open this document and view contents Learning disjunctive concepts using domain knowledge - Harish Ragavan and Larry Rendell
open this document and view contents Average case analysis of k-CNF and k-DNF learning algorithms - Daniel S. Hirschberg, Michael J. Pazzani and Kamal M. Ali
open this document and view contents Co-learning of total recursive functions - R. Freivalds, M. Karpinski and C. H. Smith
open this document and view contents Efficient Learning of Regular Expressions from Good Examples - Alvis Brāzma and Kārlis Čerāns
open this document and view contents An optimal-control application of two paradigms of on-line learning - V. G. Vovk
open this document and view contents Data-driven inductive inference of finite-state automata - J. Gregor
open this document and view contents A modular Q-learning architecture for manipulator task decomposition - Chen K. Tham and Richard W. Prager
open this document and view contents A constraint-based induction algorithm in FOL - Michèle Sebag
open this document and view contents An algorithm to learn read-once threshold formulas, and transformations between learning models - N. Bshouty, T. Hancock, L. Hellerstein and M. Karpinski
open this document and view contents The Importance of Attribute Selection Measures in Decision Tree Induction - W. Z. Liu and A. P. White
open this document and view contents Learning one-dimensional geometric patterns under one-sided random misclassification noise - P. W. Goldberg and S. A. Goldman
open this document and view contents Tracking drifting concepts by minimizing disagreements - David P. Helmbold and Philip M. Long
open this document and view contents Learning nonoverlapping perceptron networks from examples and membership queries - Thomas R. Hancock, Mostefa Golea and Mario Marchand
open this document and view contents Learning Default Concepts - Dale Schuurmans and Russell Greiner
open this document and view contents Bayesian inductive logic programming - S. Muggleton
open this document and view contents Using genetic search to refine knowledge-based neural networks - David W. Opitz and Jude W. Shavlik
open this document and view contents Training Digraphs - Hsieh-Chang Tu and Carl H. Smith
open this document and view contents In defense of C4.5: notes on learning one-level decision trees - Tapio Elomaa
open this document and view contents Weight elimination and effective network size - Andreas S. Weigend and David E. Rumelhart
open this document and view contents Learning with malicious membership queries and exceptions - D. Angluin and M. Kriķis
open this document and view contents Some New Directions in Computational Learning Theory - M. Frazier and L. Pitt
open this document and view contents The Neural Network Loading Problem is Undecidable - H. Wiklicky
open this document and view contents Program Size Restrictions in Computational Learning - Sanjay Jain and Arun Sharma
open this document and view contents Using neural networks to modularize software - Robert W. Schwanke and Joseé Stephen Hanson
open this document and view contents Recent advances in inductive logic programming - S. Muggleton
open this document and view contents Learning Boolean formulas - Michael Kearns, Ming Li and Leslie Valiant
open this document and view contents Geometrical concept learning and convex polytopes - T. Hegedüs
open this document and view contents Introduction to the Abstracts of the Invited Talks Presented at ML92 Conference in Aberdeen, 1-3 July 1992 - D. Sleeman
open this document and view contents An optimal parallel algorithm for learning DFA - J. L. Balcázar, J. Díaz, R. Gavaldà and O. Watanabe
open this document and view contents The Learnability of Description Logics with Equality Constraints - William W. Cohen and Haym Hirsh
open this document and view contents Evaluation of learning biases using probabilistic domain knowledge - Marie desJardins
open this document and view contents Using sampling and queries to extract rules from trained neural networks - Mark W. Craven and Jude W. Shavlik
open this document and view contents Algebraic Reasoning about Reactions: Discovery of Conserved Properties in Particle Physics - Raúl E. Valdés-Pérez
open this document and view contents Case-Based Learning: Predictive Features in Indexing - C. M. Seifert, K. J. Hammond, H. M. Johnson, T. M. Converse, T. F. Mcdoughal and S. W. Vanderstoep
open this document and view contents How loading complexity is affected by node function sets - Stephen Judd
open this document and view contents Hypothesis-Driven Constructive Induction in AQ17-HCI: A Method and Experiments - Janusz Wnek and Ryszard S. Michalski
open this document and view contents Learning Rules with Local Exceptions - J. Kivinen, H. Mannila and E. Ukkonen
open this document and view contents Efficient learning of continuous neural networks - P. Koiran
open this document and view contents Infinitary Self-Reference in Learning Theory - J. Case
open this document and view contents Learning the CLASSIC Description Logic: Theoretical and Experimental Results - William W. Cohen and Haym Hirsh
open this document and view contents Inference and minimization of hidden Markov chains - D. Gillman and M. Sipser
open this document and view contents Machine Learning of Higher Order Programs - G. Baliga, J. Case, S. Jain and M. Suraj
open this document and view contents On a learnability question associated to neural networks with continuous activations - B. DasGupta, H. T. Siegelmann and E. Sontag
open this document and view contents Toward an ideal trainer - Susan L. Epstein
open this document and view contents On Case-Based Representability and Learnability of Languages - Christoph Globig and Steffen Lange
open this document and view contents Weakly Learning DNF and Characterizing Statistical Query Learning Using Fourier Analysis - A. Blum, M. Furst, J. Jackson, M. Kearns, Y. Mansour and S. Rudich
open this document and view contents On learning read-k-satisfy-j DNF - A. Blum, R. Khardon, E. Kushilevitz, L. Pitt and D. Roth
open this document and view contents Vacillatory learning of nearly-minimal size grammars - John Case, Sanjay Jain and Arun Sharma
open this document and view contents An inductive inference appraoch to classification - R. Freivalds and A. Hoffmann
open this document and view contents An incremental concept formation approach for learning from databases - Robert Godin and Rokia Missaoui
open this document and view contents Recent Methods for RNA Modeling Using Stochastic Context-Free Grammars - Yasubumi Sakakibara, Michael Brown, Richard Hughey, I. Saira Mian, Kimmen Sjölander, Rebecca C. Underwood and David Haussler
open this document and view contents Irrelevant features and the subset selection problem - George H. John, Ron Kohavi and Karl Pfleger
open this document and view contents A Hidden Markov Model that finds genes in E. coli DNA - A. Krogh, I. S. Mian and D. Haussler
open this document and view contents A Note on Learning DNF Formulas Using Equivalence and Incomplete Membership Queries - Zhixiang Chen
open this document and view contents The minimum L-complexity algorithm and its applications to learning non-parametric rules - K. Yamanishi
open this document and view contents Comparing methods for refining certainty-factor rule-bases - J. Jeffrey Mahoney and Raymond J. Mooney
open this document and view contents Simulation results for a new two-armed bandit heuristic - Ronald L. Rivest and Yiqun Yin
open this document and view contents Using knowledge-based neural networks to refine roughly-correct information - Geoffrey G. Towell and Jude W. Shavlik
open this document and view contents Learnability with Restricted Focus of Attention Guarantees Noise-Tolerance - Shai Ben-David and Eli Dichterman
open this document and view contents Learning with Higher Order Additional Information - Ganesh Baliga and John Case
open this document and view contents Three Decades of Team Learning - Carl H. Smith
open this document and view contents Synthesis Algorithm for Recursive Processes by mu-calculus - Shigemoto Kimura, Atsushi Togashi and Norio Shiratori
open this document and view contents Learning theoretical terms - Ranan B. Banerji
open this document and view contents An improved algorithm for incremental induction of decision trees - Paul E. Utgoff
open this document and view contents Oracles and queries that are sufficient for exact learning - N. H. Bshouty, R. Cleve, S. Kannan and C. Tamon
open this document and view contents Bayes decisions in a neural network-PAC setting - Svetlana Anulova, Jorge R. Cuellar, Klaus-U. Höffgen and Hans-U. Simon
open this document and view contents A Polynomial Approach to the Constructive Induction of Structural Knowledge - Jörg-Uwe Kietz and Katharina Morik
open this document and view contents Trial and Error: a New Approach to Space-bounded Learning - F. Ameur, P. Fischer, K. U. Höffgen and F. Meyer auf der Heide
open this document and view contents Unsupervised learning for mobile robot navigation using probabilistic data association - Ingemar J. Cox and John J. Leonard
open this document and view contents Learning in abstraction space - George Drastal
open this document and view contents Bias in Information-Based Measures in Decision Tree Induction - Allan P. White and Wei Zhong Liu
open this document and view contents Trading accuracy for simplicity in decision trees - Marko Bohanec and Ivan Bratko
open this document and view contents Learning with discrete multivalued neurons - Zoran Obradović and Ian Parberry
open this document and view contents Learning unions of boxes with membership and equivalence queries - P. W. Goldberg, S. A. Goldman and H. D. Mathais
open this document and view contents When are k-nearest neighbor and backpropagation accurate for feasible-sized sets of examples? - Eric. B. Baum
open this document and view contents Knowledge Acquisition from Amino Acid Sequences by Machine Learning System BONSAI - S. Shimozono, A. Shinohara, T. Shinohara, S. Miyano, S. Kuhara and S. Arikawa
open this document and view contents TD(lambda) converges with probability 1 - Peter Dayan and Terrence J. Sejnowski
open this document and view contents Lower bounds on the VC-dimension of smoothly parametrized function classes - W. S. Lee, P. L. Bartlett and R. C. Williamson
open this document and view contents Frequencies vs biases: machine learning problems in natural language processing - abstract - Fernando C. N. Pereira
open this document and view contents Flattening and Saturation: Two Representation Changes for Generalization - Céline Rouveirol
open this document and view contents Combining symbolic and neural learning, extended abstract - Jude Shavlik
open this document and view contents Learning from a consistently ignorant teacher - M. Frazier, S. Goldman, N. Mishra and L. Pitt
open this document and view contents Bounded degree graph inference from walks - Vijay Raghavan
open this document and view contents Approximation and estimation bounds for artificial neural networks - Andrew R. Barron
open this document and view contents On the limits of proper learnability of subclasses of DNF formulas - K. Pillaipakkamnatt and V. Raghavan
open this document and view contents Explicit Representation of Concept Negation - Jean-Francois Puget
open this document and view contents Guest Editor's Introduction - Michael J. Pazzani
open this document and view contents Efficient reinforcement learning - C. N. Fiechter
open this document and view contents Neural Networks: a Comprehensive Foundation - S. Haykin
open this document and view contents Proceedings of the Seventh Annual ACM Conference on Computational Learning Theory - Manfred Warmuth
open this document and view contents Prototype and feature selection by sampling and random mutation hill climbing algorithms - David B. Skalak
open this document and view contents On learning discretized geometric concepts - N. Bshouty
open this document and view contents Probabilistic hill-climbing - William W. Cohen, Russell Greiner and Dale Schuurmans
open this document and view contents Efficient algorithms for minimizing cross validation error - Andrew W. Moore and Mary S. Lee
open this document and view contents Efficient NC algorithms for set cover with applications to learning and geometry - Bonnie Berger, John Rompel and Peter W. Shor
open this document and view contents Rich Classes Inferable from Positive Data: Length-Bounded Elementary Formal Systems - Takeshi Shinohara
open this document and view contents Learning hard concepts through constructive induction: framework and rationale - Larry Rendell and Raj Seshu
open this document and view contents The power of probabilism in popperian FINite learning - R. Daley, B. Kalyanasundaram and M. Velauthapillai
open this document and view contents Stochastic Context-Free Grammars for tRNA modeling - Yasubumi Sakakibara, Michael Brown, Richard Hughey, I. Saira Mian, Kimmen Sjölander, Rebecca C. Underwood and David Haussler
open this document and view contents Markov games as a framework for multi-agent reinforcement learning - Michael L. Littman
open this document and view contents Learning fixed point patterns by recurrent networks - Leong Kwan Li
open this document and view contents The generate, test, and explain discovery system architecture - Michael de la Maza
open this document and view contents Playing the matching-shoulders lob-pass game with logarithmic regret - J. Kilian, K. J. Lang and B. A. Pearlmutter
open this document and view contents On the perceptron learning algorithm on data with high precision - Kai-Yeung Siu, Amir Dembo and Thomas Kailath
open this document and view contents Fuzzy Analogy Based Reasoning and Classification of Fuzzy Analogies - Toshiharu Iwatani, Shun'ichi Tano, Atsushi Inoue and Wataru Okamoto
open this document and view contents Weakening the language bias in LINUS - N. Lavrac and S. Džeroski
open this document and view contents Generalization in partially connected layered neural networks - K. H. Kwon, K. Kang and J. H. Oh
open this document and view contents Inductive Inference of Prolog Programs with linear dependency from positive data - H. Arimura and T. Shinohara
open this document and view contents Projection pursuit learning: some theoretical issues - Ying Zhao and Christopher G. Atkeson
open this document and view contents Improved Sample Size Bounds for PAB-decisions - S. Pölt
open this document and view contents Detecting structure in small datasets by network fitting under complexity constraints - W. Finnoff and H. G. Zimmermann
open this document and view contents Refinements of Inductive Inference by Popperian and Reliable Machines - John Case, Sanjay Jain and Suzanne Ngo-Manguelle
open this document and view contents Inference of context-free grammars by enumeration: Structural containment as an ordering bias - J. Y. Giordano
open this document and view contents Introduction Structured Connectionist Systems - Alex Waibel
open this document and view contents Finding Minimal Generalizations for Unions of Pattern Languages and Its Application to Inductive Inference from Positive Data - H. Arimura, T. Shinohara and S. Otsuki
open this document and view contents The weighted majority algorithm - N. Littlestone and M. K. Warmuth
open this document and view contents Learning Concatenations of Locally Testable Languages from Positive Data - Satoshi Kobayashi and Takashi Yokomori
open this document and view contents Approximate Inference and Scientific Method - M. A. Fulk and S. Jain
open this document and view contents Book Review: C4.5: Programs for Machine Learning by J. Ross Quinlan. Morgan Kaufmann Publishers, Inc., 1993. - Steven L. Salzberg
open this document and view contents Towards efficient inductive synthesis from input/output examples - Jānis Barzdinš
open this document and view contents Children, adults, and machines as discovery systems - David Klahr
open this document and view contents Composite Geometric Concepts and Polynomial Predictability - P. M. Long and M. K. Warmuth
open this document and view contents Learning disjunctive concepts by means of genetic algorithms - Attilio Giordana, Lorenza Saitta and Floriano Zini
open this document and view contents Regular grammatical inferencefrom positive and negative samples by genetic search: The GIG method - P. Dupon
open this document and view contents Associative Reinforcement Learning: A Generate and Test Algorithm - Leslie Pack Kaelbling
open this document and view contents Ignoring data may be the only way to learn efficiently - R. Wiehagen and T. Zeugmann
open this document and view contents Towards a better understanding of memory-based reasoning systems - John Rachlin, Simon Kasif, Steven Salzberg and David W. Aha
open this document and view contents Rule-Generating Abduction for Recursive Prolog - Kouichi Hirata
open this document and view contents A schema for using multiple knowledge - Matjaž Gams, Marko Bohanec and Bojan Cestnik
open this document and view contents Learning properties of multi-layer perceptrons with and without feedback - D. Gawronska, B. Schürmann and J. Hollatz
open this document and view contents On learning arithmetic read-once formulas with exponentiation - D. Bshouty and N. H. Bshouty
open this document and view contents PAC learning with irrelevant attributes - Aditi Dhagat and Lisa Hellerstein
open this document and view contents A Formal Model of Hierarchical Concept-Learning - R. L. Rivest and R. Sloan
open this document and view contents Rigorous learning curve bounds from statistical mechanics - D. Haussler, M. Kearns, H. S. Seung and N. Tishby
open this document and view contents Discrete Sequence Prediction and Its Applications - Philip Laird and Ronald Saul
open this document and view contents Experience with a Learning Personal Assistant - Tom M. Mitchell, Rich Caruana, Dayne Freitag, John P. McDermott and David Zabowski
open this document and view contents Binary decision trees and an 'average-case' model for concept learning: implications for feature construction and the study of bias - Raj Seshu
open this document and view contents Learning Non-parametric Smooth Rules by Stochastic Rules with Finite Partitioning - K. Yamanishi
open this document and view contents A conservation law for generalization performance - Cullen Shaffer
open this document and view contents Learning from data with bounded inconsistency: theoretical and experimental results - Haym Hirsh and William W. Cohen
open this document and view contents The inference of tree languages from finite samples: an algebraic approach - Timo Knuutila and Magnus Steinby
open this document and view contents Asynchronous Stochastic Approximation and Q-Learning - John N. Tsitsiklis
open this document and view contents Acquiring and Combining Overlapping Concepts - Joel D. Martin and Dorrit O. Billman
open this document and view contents A connectionist model of the learning of personal pronouns in English - Thomas R. Shultz, David Buckingham and Yuriko Oshima-Takane
open this document and view contents Combining Symbolic and Neural Learning - Jude W. Shavlik
open this document and view contents On learning discretized geometric concepts - Nader H. Bshouty, Zhixiang Chen and Steve Homer
open this document and view contents Extremes in the Degrees of Inferability - L. Fortnow, W. Gasarch, S. Jain, E. Kinber, M. Kummer, S. Kurtz, M. Pleszkoch, T. Slaman, R. Solovay and F. Stephan
open this document and view contents Revision of production system rule-bases - Patrick M. Murphy and Michael J. Pazzani
open this document and view contents Frequencies vs. biases: machine learning problems in natural language processing - abstract - F. C. N. Pereira
open this document and view contents Learning from Examples with Typed Equational Programming - Akira Ishino and Akihiro Yamamoto
open this document and view contents Prototype selection using competitive learning - Michael Lemmon
open this document and view contents A Bayesian framework to integrate symbolic and neural learning - Irina Tchoumatchenko and Jean-Gabriel Ganascia
open this document and view contents Consideration of risk in reinforcement learning - Matthias Heger
open this document and view contents To discount or not to discount in reinforcement learning: a case study comparing R learning and Q learning - Sridhar Mahadevan
open this document and view contents Language Learning from Good Examples - Steffen Lange, Jochen Nessel and Rolf Wiehagen
open this document and view contents A powerful heuristic for the discovery of complex patterned behavior - Raúl E. Valdés-Pérez and Aurora Pérez
open this document and view contents Randomly Fallible Teachers: Learning Monotone DNF with an Incomplete Membership Oracle - Dana Angluin and Donna K. Slonim
open this document and view contents Learning an Optimally Accurate Representation System - Russell Greiner and Dale Schuurmans
open this document and view contents Logic and Learning - Daniel N. Osherson, Michael Stob and Scott Weinstein
open this document and view contents Higher-Order Neural Networks Applied to 2D and 3D Object Recognition - Lilly Spirkovska and Max B. Reid
open this document and view contents Incorporating prior knowledge into networks of locally-tuned units - Martin Röscheisen, Reimar Hoffman and Volker Tresp
open this document and view contents An Introduction to Computational Learning Theory - Michael J. Kearns and Umesh V. Vazirani
open this document and view contents Refining algorithms with knowledge-based neural networks: improving the Cho-Fasman algorithm for protein folding - Richard Maclin and Jude W. Shavlik
open this document and view contents Simulating the Child's Acquisition of the Lexicon and Syntax - Experiences with Babel - Rick Kazman
open this document and view contents A hierarchy of language families learnable by regular language learners - Yuji Takada
open this document and view contents Efficient Algorithm for Learning Simple Regular Expressions from Noisy Examples - Alvis Brāzma
open this document and view contents Probability density estimation and local basis function neural networks - Padhraic Smyth
open this document and view contents Generalized stochastic complexity and its applications to learning - Kenji Yamanishi
open this document and view contents Learning Unions of Convex Polygons - P. Fischer
open this document and view contents Incremental abductive EBL - William W. Cohen
open this document and view contents On Training Simple Neural Networks and Small-weight Neurons - T. Hegedüs
open this document and view contents An upper bound on the loss from approximate optimal-value functions - Satinder P. Singh and Richard C. Yee
open this document and view contents Average-Case Analysis of Pattern Language Learning Algorithms - Thomas Zeugmann
open this document and view contents Learning linear threshold functions in the presence of classification noise - T. Bylander
open this document and view contents Combining top-down and bottom-up techniques in inductive logic programming - John M. Zelle, Raymond J. Mooney and Joshua B. Konvisser
open this document and view contents Classification Using Information - William I. Gasarch, Mark G. Pleszkoch and Mahendran Velauthapillai
open this document and view contents On monotonic strategies for learning r.e.\ languages - Sanjay Jain and Arun Sharma
open this document and view contents Learning structurally reversible context-free grammars from queries and counterexamples in polynomial time - A. Burago
open this document and view contents Learning Local and Recognizable omega-languages and Monadic Logic Programs - A. Saoudi
open this document and view contents The minimum description length principle and categorical theories - J. R. Quinlan
open this document and view contents Learning with instance-based encodings - Henry Tirri
open this document and view contents Efficient inference of partial types - Dexter Kozen, Jens Palsberg and Michael I. Schwartzbach
open this document and view contents Efficient distribution-free learning of probabilistic concepts - Michael J. Kearns and Robert E. Schapire
open this document and view contents On the learnability of discrete distributions - M. Kearns, Y. Mansour, D. Ron, R. Rubinfeld, R. Schapire and L. Sellie
open this document and view contents Improving generalization with active learning - David Cohn, Les Atlas and Richard Ladner
open this document and view contents Deductive Plan Generation - Wolfgang Bibel and Michael Thielscher
open this document and view contents Concept Formation During Interactive Theory Revision - Stefan Wrobel
open this document and view contents Selective reformulation of examples in concept learning - Jean-Daniel Zucker and Jean-Gabriel Ganascia
open this document and view contents Inductive inference of recursive concepts - Yasuhito Mukouchi
open this document and view contents Exploiting random walks for learning - P. L. Bartlett, P. Fischer and K.-U. Höffgen
open this document and view contents Refutably Probably Approximately Correct Learning - Satoshi Matsumoto and Ayumi Shinohara
open this document and view contents An incremental learning approach for completable planning - Melinda T. Gervasio and Gerald F. DeJong
open this document and view contents Acquisition of Children's Addition Strategies: A Model of Impasse-Free, Knowledge-Level Learning - Randolph M. Jones and Kurt Vanlehn
open this document and view contents On-line learning from search failures - Neeraj Bhatnagar and Jack Mostow
open this document and view contents Characterization of language learning from informant under various monotonicity constraints - S. Lange and T. Zeugmann
open this document and view contents Learning without state-estimation in partially observable Markovian decision processes - Satinder P. Singh, Tommi Jaakkola and Michael I. Jordan
open this document and view contents Matters Horn and Other Features in the Computational Learning Theory Landscape: The Notion of Membership - M. Frazier
open this document and view contents VC dimension and sampling complexity of learning sparse polynomials and rational functions - Marek Karpinski and Thorsten Werther
open this document and view contents Learning recursive relations with randomly selected small training sets - David W. Aha, Stephanie Lapointe, Charles X. Ling and Stan Matwin
open this document and view contents Guest Editorial - Katharina Morik, Francesco Bergadano and Wray Buntine
open this document and view contents Comparing connectionist and symbolic learning methods - J. R. Quinlan
open this document and view contents Characterizing language identification by standardizing operations - Sanjay Jain and Arun Sharma
open this document and view contents Technical note: statistical methods for analyzing speedup learning experiments - Oren Etzioni and Ruth Etzioni
open this document and view contents Mutual information gaining algorithm and its relation to PAC-learning algorithm - Eiji Takimoto, Ichiro Tajika and Akira Maruoka
open this document and view contents Associative Reinforcement Learning: Functions in k-DNF - Leslie Pack Kaelbling
open this document and view contents Co-learnability and FIN-identifiability of enumerable classes of total recursive functions - R. Freivalds, Dace Gobleja, Marek Karpinski and Carl H. Smith
open this document and view contents Nonuniform learnability - Gyora M. Benedek and Alon Itai
open this document and view contents The representation of recursive languages and its impact on the efficiency of learning - S. Lange
open this document and view contents Monotonicity versus Efficiency for Learning Languages from Texts - Efim Kinber
open this document and view contents Greedy attribute selection - Rich Caruana and Dayne Freitag
open this document and view contents Derived Sets and Inductive Inference - Kalvis Aps\=ıtis
open this document and view contents On the Power of Equivalence Queries - R. Gavaldà
Februaryopen this document and view contents Hidden Markov models in computational biology: Applications to protein modeling - A. Krogh, M. Brown, I. S. Mian, K. Sjölander and D. Haussler
Marchopen this document and view contents Exact learning of mu-DNF formulas with malicious membership queries - Dana Angluin
open this document and view contents On Using the Fourier transform to learn disjoint DNF - R. Khardon
open this document and view contents Optimal Sequential Probability Assignment for Individual Sequences - M. J. Weinberger, N. Merhav and M. Feder
Juneopen this document and view contents Exponentiated Gradient Versus Gradient Descent for Linear Predictors - J. Kivinen and M. K. Warmuth
Julyopen this document and view contents Bounds on approximate steepest descent for likelihood maximization in exponential families - N. Cesa-Bianchi, A. Krogh and M. K. Warmuth
Augustopen this document and view contents Optimally Parsing a Sequence into Different Classes Based on Multiple Types of Information - G. D. Stormo and D. Haussler
open this document and view contents RNA Modeling Using Gibbs Sampling and Stochastic Context Free Grammars - L. Grate, M. Herbster, R. Hughey, I. S. Mian, H. Noller and D. Haussler
Octoberopen this document and view contents 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 - Setsuo Arikawa and Klaus P. Jantke
Decemberopen this document and view contents Hinfinity Bounds for the recursive-least-squares algorithm - B. Hassibi and T. Kailath