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1951-1967 1968-1972 1973-1974 1975 1976 1977 1978 1979 1980-1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002-Circa 13200000
1989open this document and view contents Representation Propoerties of Networks: Kolmogorov's Theorm Is Irrelevant - T. Poggio and F. Girosi
open this document and view contents Training sequences - Dana Angluin, William I. Gasarch and Carl H. Smith
open this document and view contents Learning read-once formulas using membership queries - L. Hellerstein and M. Karpinski
open this document and view contents On Learning Sets and Functions - B. K. Natarajan
open this document and view contents On the error probabilty of boolean concept descriptions - F. Bergadano and L. Saitta
open this document and view contents Consistent inference of probabilities in layered networks: predictions and generalizations - N. Tishby, E. Levin and S. Solla
open this document and view contents A polynomial-time algorithm for learning k-variable pattern languages from examples - M. Kearns and L. Pitt
open this document and view contents An application of minimum description length principle to online recognition of handprinted alphanumerals - Q. Gao and M. Li
open this document and view contents A Reconfigurable Analog (VLSI Neural Network Chip - H. P. Graf, S. Satyanarayana and Y. Tsividis
open this document and view contents Incremental Induction of Decision Trees - Paul E. Utgoff
open this document and view contents A Heuristic Approach to the Discovery of Macro-operators - Glenn A. Iba
open this document and view contents The Knowledge Level Reinterpreted: Modeling How Systems Interact - William J. Clancey
open this document and view contents Erratum one - Authorless
open this document and view contents Probabilistic Inductive Inference - L. Pitt
open this document and view contents Learnability and Linguistic Theory - R. J. Matthews and W. Demopoulos
open this document and view contents Learning Arm Kinematics and Dynamics - C. G. Atkeson
open this document and view contents Neural networks, principle components, and subspaces - E. Oja
open this document and view contents Stochastic Complexity in Statistical Inquiry - J. Rissanen
open this document and view contents Polynomial learning of semilinear sets - N. Abe
open this document and view contents Bounding sample size with the Vapnik-Chervonenkis dimension - J. Shawe-Taylor, M. Anthony and R. L. Biggs
open this document and view contents The equivalence and learning of probabilistic automata - W. Tzeng
open this document and view contents Genetic Algorithms in Search, Optimization, and Machine Learning - D. E. Goldberg
open this document and view contents Models of Incremental Concept Formation - John H. Gennari, Pat Langley and Doug Fisher
open this document and view contents From on-line to batch learning - N. Littlestone
open this document and view contents Learnability and the Vapnik-Chervonenkis Dimension - Anselm Blumer, Andrzej Ehrenfeucht, David Haussler and Manfred K. Warmuth
open this document and view contents Identifying mu-decision trees and mu-formulas with constrained instance queries - T. Hancock
open this document and view contents The World Would Be a Better Place if Non-Programmers Could Program - John McDermott
open this document and view contents Knowledge of an Upper Bound on Grammar Size Helps Language Learning - S. Jain and A. Sharma
open this document and view contents The light bulb problem - R. Paturi, S. Rajasekaran and J. Reif
open this document and view contents On approximate truth - D. N. Osherson, M. Stob and S. Weinstein
open this document and view contents Approximation by Superpositions of a Sigmoidal Function - G. Cybenko
open this document and view contents Synthetic Neural Modelling: Comparisons of Population and Connectionist Approaches - Jr G. N. Reeke, O. Sporns and G. M. Edelman
open this document and view contents Automated Knowledge Acquisition for Strategic Knowledge - Thomas R. Gruber
open this document and view contents Identifying decision trees with equivalence queries - T. Hancock
open this document and view contents Semi-Supervised Learning - R. A. Board and L. Pitt
open this document and view contents A greedy method for learning mu-DNF functions under the uniforn distribution - G. Pagallo and D. Haussler
open this document and view contents What Size Net Gives Valid Generalization? - E. Baum and D. Haussler
open this document and view contents A parametrization scheme for classifying models of learnability - S. Ben-David, G. M. Benedek and Y. Mansour
open this document and view contents On Characterizing and Learning Some Classes of Read-once Functions - L. Hellerstein
open this document and view contents Reliable and useful learning - J. Kivinen
open this document and view contents A theory of learning simple concepts under simple distributions and average case complexity for the universal distribution - M. Li and P. M. B. Vitanyi
open this document and view contents Optimal unsupervised learning in a single-layer linear feedforward neural network - T. D. Sanger
open this document and view contents The CN2 Induction Algorithm - Peter Clark and Tim Niblett
open this document and view contents Task-Structures, Knowledge Acquisition and Learning - B. Chandrasekaran
open this document and view contents Learning Decision Trees from Random Examples - A. Ehrenfeucht and D. Haussler
open this document and view contents Learning Automata - An Introduction - K. S. Narendra and M. A. L. Thathachar
open this document and view contents Toward a Unified Science of Machine Learning - P. Langley
open this document and view contents A Critique of the Valiant Model - W. Buntine
open this document and view contents Efficient Specialization of Relational Concepts - Kurt Vanlehn
open this document and view contents Supporting Start-to-Finish Development of Knowledge Bases - Ray Bareiss, Bruce W. Porter and Kenneth S. Murray
open this document and view contents Probably-Approximate Learning over Classes of Distributions - B. K. Natarajan
open this document and view contents Polynomial Learnability as a Formal Model of Natural Language Acquisition - Naoki Abe
open this document and view contents Conceptual Clustering, Categorization, and Polymorphy - Stephen José Hanson and Malcolm Bauer
open this document and view contents Fast Learning in Multi-Resolution Hierarchies - J. Moody
open this document and view contents Equivalence queries and approximate fingerprints - D. Angluin
open this document and view contents Performance of a Stochastic Learning Chip - J. Alspector and R. B. Allen
open this document and view contents Complexity issues in learning by neural nets - J. Lin and J. S. Vitter
open this document and view contents Knowledge Acquisition for Knowledge-Based Systems: Notes on the State-of-the-Art - John H. Boose and Brian R. Gaines
open this document and view contents Trade-Off Among Parameters Affecting Inductive Inference - R. Freivalds, C. H. Smith and M. Velauthapillai
open this document and view contents Automated Support for Building and Extending Expert Models - Mark A. Musen
open this document and view contents Inductive inference with bounded number of mind changes - M. Velauthapillai
open this document and view contents Fast Learning in Networks of Locally-Tuned Processing Units - J. Moody and C. Darken
open this document and view contents Learning nested differences of intersection-closed concept classes - D. Helmbold, R. Sloan and M. K. Warmuth
open this document and view contents LT Revisited: Explanation-Based Learning and the Logic of Principia Mathematica - Paul O'Rorke
open this document and view contents Inductive Inference From Good Examples - R. Freivalds, E. B. Kinber and R. Wiehagen
open this document and view contents Learning Conjunctive Concepts in Structural Domains - D. Haussler
open this document and view contents Elementary formal system as a unifying framework for language learning - S. Arikawa, T. Shinohara and A. Yamamoto
open this document and view contents Constant depth circuits, Fourier transform, and learnability - N. Linial, Y. Mansour and N. Nisan
open this document and view contents On learning from exercises - B. K. Natarajan
open this document and view contents Proceedings of the Second Annual Workshop on Computational Learning Theory - Ronald Rivest and David Haussler and Manfred K. Warmuth
open this document and view contents Learning under uniform distribution - A. Marchetti-Spaccamela and M. Protasi
open this document and view contents Learning simple deterministic languages - H. Ishizaka
open this document and view contents Some Results on Learning - B. K. Natarajan
open this document and view contents An Empirical Comparison of Selection Measures for Decision-Tree Induction - John Mingers
open this document and view contents Using queries to identify mu-formulas - D. Angluin
open this document and view contents On the complexity of learning from counterexamples - W. Maass and G. Turán
open this document and view contents Synergy of clustering multiple backpropagation networks - N. Lincoln and J. Skrzypek
open this document and view contents Generalizing the PAC model: sample size bounds from metric dimension-based uniform convergence results - D. Haussler
open this document and view contents Recursion Theoretic Characterizations of Language Learning - S. Jain and A. Sharma
open this document and view contents Cryptographic limitations on learning Boolean formulae and finite automata - M. Kearns and L. G. Valiant
open this document and view contents Monte-Carlo Inference and its Relations to Reliable Frequency Identification - Efim Kinber and Thomas Zeugmann
open this document and view contents Training a 3-node neural net is NP-Complete - A. Blum and R. L. Rivest
open this document and view contents When Will Machines Learn? - Douglas B. Lenat
open this document and view contents An Empirical Comparison of Pruning Methods for Decision Tree Induction - John Mingers
open this document and view contents A general lower bound on the number of examples needed for learning - A. Ehrenfeucht, D. Haussler, M. Kearns and L. Valiant
open this document and view contents The Vapnik-Chervonenkis Dimension: Information verses Complexity in Learning - Y. S. Abu-Mostafa
open this document and view contents Mistake Bounds and Logarithmic Linear-threshold Learning Algorithms - N. Littlestone
open this document and view contents Space-bounded learning and the Vapnik-Chervonenkis dimension - S. Floyd
open this document and view contents Efficient NC algorithms for set cover with applications to learning and geometry - B. Berger, J. Rompel and P. W. Shor
open this document and view contents A Study of Explanation-Based Methods for Inductive Learning - Nicholas S. Flann and Thomas G. Dietterich
open this document and view contents A Statistical Approach to Learning and Generalization in Neural Networks - E. Levin, N. Tishby and S. Solla
open this document and view contents A Parallel Network that Learns to Play Backgammon - G. Tesauro and T. J. Sejnowski
open this document and view contents Planning and learning in permutation groups - A. Fiat, S. Moses, A. Shamir, I. Shimshoni and G. Tardos
open this document and view contents Learning structure from data: a survey - J. Pearl and R. Dechter
open this document and view contents Can Machine Learning Offer Anything to Expert Systems? - Bruce G. Buchanan
open this document and view contents Induction from the general to the more general - K. T. Kelly
open this document and view contents Refined Query Inference - E. B. Kinber and T. Zeugmann
open this document and view contents Inductive inference, DFAs, and computational complexity - L. Pitt
open this document and view contents Learning Faster than Promised by the Vapnik-Chervonenkis Dimension - A. Blumer and N. Littlestone
open this document and view contents Convergence to nearly minimal size grammars by vacillating learning machines - S. Jain, A. Sharma and J. Case
open this document and view contents On the role of search for learning - S. A. Kurtz and C. H. Smith
open this document and view contents Adaptive Neural Networks Using MOS Charge Storage - D. B. Schwartz, R. E. Howard and W. E. Hubbard
open this document and view contents Identification of unions of languages drawn from an identifiable class - K. Wright
open this document and view contents Informed parsimonious inference of prototypical genetic sequences - A. Milosavljevi'c, D. Haussler and J. Jurka
open this document and view contents Computational Learning Theory: New Models and Algorithms - R. H. Sloan
open this document and view contents On Metric Entripy, Vapnik-Chervonenkis Dimension, and Learnability for a Class of Distributions - S. Kulkarni
open this document and view contents Regressiveness - M. Fulk
open this document and view contents Deterministic Boltzmann Learning Performs Steepest Descent in Weight-Space - G. E. Hinton
Februaryopen this document and view contents Approximation of Boolean functions by sigmoidal networks: Part I: XOR and other two-variable functions - E. K. Blum
open this document and view contents Backpropagation Can Give Rise to Spurious Local Minima Even for Networks without Hidden Layers - E. D. Sontag and H. J. Sussmann
Marchopen this document and view contents Inferring Decision Trees Using the Minimum Description Length Principle - J. R. Quinlan and R. L. Rivest
Mayopen this document and view contents The Use of Artificial Neural Networks for Phonetic Recognition - H. C. Leung
open this document and view contents Back Propagation Fails to Separate Where Perceptrons Succeed - M. L. Brady, R. Raghavan and J. Slawny
open this document and view contents Learning from Delayed Rewards - C. J. C. H. Watkins
open this document and view contents The Computational Complexity of Machine Learning - M. Kearns
open this document and view contents On the Computational Complexity of Training Simple Neural Networks - A. Blum
Juneopen this document and view contents Tensor Manipulation Networks: Connectionist and Symbolic Approaches to Comprehension, Learning, and Planning - C. P. Dolan
open this document and view contents Finding Natural Clusters Through Entropy Minimization - R. S. Wallace
open this document and view contents Neural Network Learning: Effects of Network and Training Set Size - N. Perugini
Julyopen this document and view contents A `Neural' Network that Learns to Play Backgammon - G. Tesauro and T. J. Sejnowski
Augustopen this document and view contents Learning in the Presence of Inaccurate Information - M. A. Fulk and S. Jain
open this document and view contents Accelerated Backpropagation Learning: Two Optimization Methods - R. Battiti
open this document and view contents Inductive Principles of the Search for Empirical Dependences (Methods Based on Weak Convergence of Probability Measures) - V. N. Vapnik
Septemberopen this document and view contents Made-up Minds: A Constructivist Approach to Artificial Intelligence - G. L. Drescher
open this document and view contents Generalizing the PAC Model for Neural Net and Other Learning Applications - D. Haussler
Octoberopen this document and view contents Analogical and Inductive Inference, International Workshop AII '89. Reinhardsbrunn Castle, GDR, October 1989, Proceedings - K. P. Jantke
open this document and view contents Towards Representation Independence in PAC-learning - M. K. Warmuth
open this document and view contents An Experimental Comparison of Connectionist and Conventional Classification Systems on Natural Data - P. C. Woodland and S. G. Smyth
open this document and view contents Networks and the Best Approximation Property - T. Poggio and F. Girosi
Novemberopen this document and view contents Discovering the Structure of a Reactive Environment by Exploration - M. C. Mozer and J. Bachrach
open this document and view contents Learnability in the Presence of Classification Noise - Y. Sakakibara
Decemberopen this document and view contents Space-bounded learning and the Vapnik-Chervonenkis Dimension (Ph.D) - S. Floyd