COLT 1996

37 papers

A Bayesian/Information Theoretic Model of Bias Learning Jonathan Baxter

A Competitive Approach to Game Learning Christopher D. Rosin, Richard K. Belew

A Data-Dependent Skeleton Estimate for Learning Gábor Lugosi, Márta Pintér

A Framework for Structural Risk Minimisation John Shawe-Taylor, Peter L. Bartlett, Robert C. Williamson, Martin Anthony

A Randomized Approximation of the MDL for Stochastic Models with Hidden Variables Kenji Yamanishi

A Simple Algorithm for Learning O(log N)-Term DNF Eyal Kushilevitz

Analysis of a Simple Learning Algorithm: Learning Foraging Thresholds for Lizards Leslie Ann Goldberg

Analysis of Greedy Expert Hiring and an Application to Memory-Based Learning (Extended Abstract) Igal Galperin

Angluin's Theorem for Indexed Families of R.e. Sets and Applications Dick De Jongh, Makoto Kanazawa

Attribute-Efficient Learning in Query and Mistake-Bound Models Nader H. Bshouty, Lisa Hellerstein

Challenges in Machine Learning for Text Classification David D. Lewis

Elementary Formal Systems, Intrinsic Complexity, and Procrastination Sanjay Jain, Arun Sharma

Game Theory, On-Line Prediction and Boosting Yoav Freund, Robert E. Schapire

Graph Learning with a Nearest Neighbor Approach Sven Koenig, Yury V. Smirnov

Learning an Optimal Decision Strategy in an Influence Diagram with Latent Variables V. G. Vovk

Learning Branches and Learning to Win Closed Games Martin Kummer, Matthias Ott

Learning Changing Concepts by Exploiting the Structure of Change Peter L. Bartlett, Shai Ben-David, Sanjeev R. Kulkarni

Learning Conjunctions of Two Unate DNF Formulas (Extended Abstract): Computational and Informational Results Aaron Feigelson, Lisa Hellerstein

Learning Curve Bounds for a Markov Decision Process with Undiscounted Rewards Lawrence K. Saul, Satinder P. Singh

Learning of Depth Two Neural Networks with Constant Fan-in at the Hidden Nodes (Extended Abstract) Peter Auer, Stephen Kwek, Wolfgang Maass, Manfred K. Warmuth

On Bayes Methods for On-Line Boolean Prediction Nicolò Cesa-Bianchi, David P. Helmbold, Sandra Panizza

On Learning Width Two Branching Programs (Extended Abstract) Nader H. Bshouty, Christino Tamon, David K. Wilson

On Restricted-Focus-of-Attention Learnability of Boolean Functions Andreas Birkendorf, Eli Dichterman, Jeffrey C. Jackson, Norbert Klasner, Hans Ulrich Simon

On the Complexity of Learning from Drifting Distributions Rakesh D. Barve, Philip M. Long

On-Line Portfolio Selection Erik Ordentlich, Thomas M. Cover

PAC Learning Axis-Aligned Rectangles with Respect to Product Distributions from Multiple-Instance Examples Philip M. Long, Lei Tan

PAC Learning Intersections of Halfspaces with Membership Queries (Extended Abstract) Stephen Kwek, Leonard Pitt

PAC-like Upper Bounds for the Sample Complexity of Leave-One-Out Cross-Validation Sean B. Holden

Predicting a Binary Sequence Almost as Well as the Optimal Biased Coin Yoav Freund

Probabilistic and Team PFIN-Type Learning: General Properties Andris Ambainis

Strong Minimax Lower Bounds for Learning András Antos, Gábor Lugosi

Synthesizing Enumeration Techniques for Language Learning Ganesh R. Baliga, John Case, Sanjay Jain

The Dual DFA Learning Problem: Hardness Results for Programming by Demonstration and Learning First-Order Representations (Extended Abstract) William W. Cohen

The Importance of Convexity in Learning with Squared Loss Wee Sun Lee, Peter L. Bartlett, Robert C. Williamson

Towards Robust Model Selection Using Estimation and Approximation Error Bounds Joel Ratsaby, Ron Meir, Vitaly Maiorov

Trees and Learning Wolfgang Merkle, Frank Stephan

VC Dimension of an Integrate-and-Fire Neuron Model Anthony M. Zador, Barak A. Pearlmutter