View the documentBack Propagation Fails to Separate Where Perceptrons Succeed - M. L. Brady, R. Raghavan and J. Slawny - May 1989
View the documentBack Propagation Separates Where Perceptrons Do - E. D. Sontag and H. J. Sussmann - 1991
View the documentBackground knowledge in GA-based concept learning - Jukka Hekanaho - 1996
View the documentBackpropagation Can Give Rise to Spurious Local Minima Even for Networks without Hidden Layers - E. D. Sontag and H. J. Sussmann - February 1989
View the documentBalanced Cooperative Modeling - Katharina Morik - 1993
View the documentBayes Decision Methods - J. Pearl - June 1985
View the documentA Bayesian analysis of algorithms for learning finite functions - James Cussens - 1995
View the documentA Bayesian approach to model learning in non-Markovian environments - Nobuo Suematsu, Akira Hayashi and Shigang Li - 1997
View the documentA Bayesian framework to integrate symbolic and neural learning - Irina Tchoumatchenko and Jean-Gabriel Ganascia - 1994
View the documentBayesian inductive logic programming - S. Muggleton - 1994
View the documentA Bayesian Method for the Induction of Probabilistic Networks from Data - Gregory F. Cooper and Edward Herskovits - 1992
View the documentBayesian Methods for Adaptive Models - D. MacKay - 1992
View the documentBayesian Networks: A Model of Self-Activated Memory for Evidential Reasoning - J. Pearl - June 1985
View the documentBayesian Training of Backpropagation Networks by the Hybrid Monte Carlo Method - R. M. Neal - April 1992
View the documentA Bayesian/information theoretic model of bias learning - Jonathan Baxter - 1996
View the documentBehavior of sequential predictors of binary sequences - T. Cover - 1965
View the documentBeing taught can be faster than asking questions - Ronald L. Rivest and Yiqun L. Yin - 1995
View the documentBELLMAN STRIKES AGAIN! The growth rate of sample complexity with dimension for the nearest neighbor classifier - S. S. Venkatesh, R. R. Snapp and D. Psaltis - 1992
View the documentBEXA: A Covering Algorithm for Learning Propositional Concept Descriptions - Hendrik Theron and Ian Cloete - 1996
View the documentBeyond independence: conditions for the optimality of the simple Bayesian classifier - Pedro Domingos and Michael Pazzani - 1996
View the documentBias in Information-Based Measures in Decision Tree Induction - Allan P. White and Wei Zhong Liu - 1994
View the documentBias plus variance decomposition for zero-one loss functions - Ron Kohavi and David H. Wolpert - 1996
View the documentBias, Version Spaces, and Valiant’s Learning Framework - D. Haussler - June 1987
View the documentThe Binary Exponentiated Gradient Algorithm for Learning Linear Functions - Tom Bylander - 1997
View the documentBivariate Scientific Function Finding in a Sampled, Real-Data Testbed - Cullen Schaffer - 1993
View the documentBoltzmann Machines: Constraint Satisfaction Networks that Learn - G. E. Hinton, T. J. Sejnowski and D. H. Ackley - May 1984
View the documentBook Review - Roland J. Zito-Wolf - 1991
View the documentBook Review: C4.5: Programs for Machine Learning by J. Ross Quinlan. Morgan Kaufmann Publishers, Inc., 1993. - Steven L. Salzberg - 1994
View the documentBook review: inductive logic programming: techniques and applications - Michael Pazzani - 1996
View the documentBook Review: Neural Network Perception for Mobile Robot Guidance by Dean A. Pomerleau. Kluwer Academic Publishers, 1993. - Geoffrey Towell - 1995
View the documentA Boolean Complete Neural Model of Adaptive Behavior - S. Hampson and D. Kibler - 1983
View the documentBoolean Feature Discovery in Empirical Learning - Giulia Pagallo and David Haussler - 1990
View the documentBoosting a Weak Learning Algorithm by Majority - Y. Freund - September 1995
View the documentBoosting and other machine learning algorithms - Harris Drucker, Corinna Cortes, L. D. Jackel, Yann LeCun and Vladimir Vapnik - 1994
View the documentBoosting the margin: a new explanation for the effectiveness of voting methods - Robert E. Schapire, Yoav Freund, Peter Bartlett and Wee Sun Lee - 1997
View the documentBounded degree graph inference from walks - Vijay Raghavan - 1994
View the documentThe bounded injury priority method and the learnability of unions of rectangles - Z. Chen and S. Homer - May 1994
View the documentBounding sample size with the Vapnik-Chervonenkis dimension - J. Shawe-Taylor, M. Anthony and R. L. Biggs - 1989
View the documentBounding the Vapnik-Chervonenkis dimension of concept classes parametrized by real numbers - Paul W. Goldberg and Mark R. Jerrum - 1995
View the documentBounding VC-dimension for neural networks: progress and prospects - Marek Karpinski and Angus Macintyre - 1995
View the documentBounds for Predictive Errors in the Statistical Mechanics of in Supervised Learning - Manfred Opper and David Haussler - 1995
View the documentBounds for the computational power and learning complexity of analog neural nets - W. Maass - 1993
View the documentBounds on approximate steepest descent for likelihood maximization in exponential families - N. Cesa-Bianchi, A. Krogh and M. K. Warmuth - July 1994
View the documentBounds on the classification error of the nearest neighbor rule - John A. Drakopoulos - 1995
View the documentBounds on the Number of Examples needed for Learning Functions - H. U. Simon - 1994
View the documentBounds on the sample complexity of Bayesian learning using information theory and the VC dimension - David Haussler, Michael Kearns and Robert E. Schapire - 1994
View the documentA branch and bound conceptual clusterer - Arthur J. Nevins - 1995
View the documentA Branch and Bound Incremental Conceptual Clusterer - Arthur J. Nevins - 1995
View the documentBreaking the Probability 1/2 Barrier in FIN-type Learning - R. Daley, B. Kalyanasundaram and M. Velauthapillai - 1995
View the documentA brief look at some machine learning problems in genomics - David Haussler - 1997