2002 | | | **The Consistency of Greedy Algorithms for Classification** - *Shie Mannor, Ron Meir and Tong Zhang* |

| | | **Metric-Based Methods for Adaptive Model Selection and Regularization** - *Dale Schuurmans and Finnegan Southey* |

| | | **Maximizing Agreements and CoAgnostic Learning** - *Nader H. Bshouty and Lynn Burroughs* |

| | | **Training Invariant Support Vector Machines** - *Dennis Decoste and Bernhard Schölkopf* |

| | | **Variable Resolution Discretization in Optimal Control** - *Rémi Munos and Andrew Moore* |

| | | **How to Achieve Minimax Expected Kullback-Leibler Distance from an Unknown Finite Distribution** - *Dietrich Braess, Jürgen Forster, Tomas Sauer and Hans U. Simon* |

| | | **Approximate algorithms for neural-Bayesian approaches** - *Tom Heskes, Bart Bakker and Bert Kappen* |

| | | **Spiking neurons and the induction of finite state machines** - *Thomas Natschläger and Wolfgang Maass* |

| | | **On a Connection between Kernel PCA and Metric Multidimensional Scaling** - *Christopher K. I. Williams* |

| | | **Hardness results for neural network approximation problems** - *Peter L. Bartlett and Shai Ben-David* |

| | | **Learning Recursive Bayesian Multinets for Data Clustering by Means of Constructive Induction** - *Jose M. Peña, ose A. Lozano and Pedro Larrañaga* |

| | | **Theoretical and Experimental Evaluation of the Subspace Information Criterion** - *Masashi Sugiyama and Hidemitsu Ogawa* |

| | | **Feature Generation Using General Constructor Functions** - *Shaul Markovitch and Dan Rosenstein* |

| | | **Feedforward Neural Networks in Reinforcement Learning Applied to High-Dimensional Motor Control** - *Rémi Coulom* |

| | | **Estimating Generalization Error on Two-Class Datasets Using Out-of-Bag Estimates** - *Tom Bylander* |

| | | **Unsupervised learning in neural computation** - *Erkki Oja* |

| | | **A Second-Order Perceptron Algorithm** - *Nicolò Cesa-Bianchi, Alex Conconi and Claudio Gentile* |

| | | **On the Smallest Possible Dimension and the Largest Possible Margin of Linear Arrangements Representing Given Concept Classes Uniform Distribution** - *Jürgen Forster and Hans Ulrich Simon* |

| | | **Near-Optimal Reinforcement Learning in Polynomial Time** - *Michael Kearns and Satinder Singh* |

| | | **PAC Analogues of Perceptron and Winnow Via Boosting the Margin** - *R. Servedio* |

| | | **On the Computational Power of Boolean Decision Lists** - *Matthias Krause* |

| | | **Entropy, Combinatorial Dimensions and Random Averages** - *Shahar Mendelson and Roman Vershynin* |

| | | **Compactness and Learning of Classes of Unions of Erasing Regular Pattern Languages** - *Jin Uemura and Masako Sato* |

| | | **Consistency Queries in Information Extraction** - *Gunter Grieser, Klaus P. Jantke and Steffen Lange* |

| | | **Reflective Inductive Inference of Recursive Functions** - *Gunter Grieser* |

| | | **Bounds for the Minimum Disagreement Problem with Applications to Learning Theory** - *Nader H. Bshouty and Lynn Burroughs* |

| | | **Learning the Internet** - *Christos Papadimitriou* |

| | | **On the Eigenspectrum of the Gram Matrix and Its Relationship to the Operator Eigenspectrum** - *John Shawe-Taylor, Chris Williams, Nello Cristianini and Jaz Kandola* |

| | | **A Probabilistic Framework for SVM Regression and Error Bar Estimation** - *J. B. Gao, S. R. Gunn, C. J. Harris and M. Brown* |

| | | **Classes with Easily Learnable Subclasses** - *Sanjay Jain, Wolfram Menzel and Frank Stephan* |

| | | **Editorial: Kernel Methods: Current Research and Future Directions** - *Nello Cristianini, Colin Campbell and Chris Burges* |

| | | **Editors' Introduction** - *Nicolo Cesa-Bianchi, Masayuki Numao and Rüdiger Reischuk* |

| | | **On the Dual Formulation of Regularized Linear Systems with Convex Risk** - *Tong Zhang* |

| | | **Tracking Linear-Threshold Concepts with Winnow** - *Chris Mesterharm* |

| | | **Query by committee, linear separation and random walks** - *Shai Fine, Ran Gilad-Bachrach and Eli Shamir* |

| | | **Model Selection for Small Sample Regression** - *Olivier Chapelle, Vladimir Vapnik and Yoshua Bengio* |

| | | **The Speed Prior: A New Simplicity Measure Yielding Near-Optimal Computable Predictions** - *Jürgen Schmidhuber* |

| | | **Learning Tree Languages from Text** - *Henning Fernau* |

| | | **On the Absence of Predictive Complexity for Some Games** - *Yuri Kalnishkan and Michael V. Vyugin* |

| | | **Asymptotic Optimality of Transductive Confidence Machine** - *Vladimir Vovk* |

| | | **Performance Guarantees for Hierarchical Clustering** - *Sanjoy Dasgupta* |

| | | **A General Dimension for Approximately Learning Boolean Functions** - *Johannes Köbler and Wolfgang Lindner* |

| | | **On Learning Monotone Boolean Functions under the Uniform Distribution** - *Kazuyuki Amano and Akira Maruoka* |

| | | **Merging Uniform Inductive Learners** - *Sandra Zilles* |

| | | **Building a Basic Block Instruction Scheduler with Reinforcement Learning and Rollouts** - *Amy McGovern, Eliot Moss and Andrew G. Barto* |

| | | **Localized Rademacher Complexities** - *Peter L. Bartlett, Olivier Bousquet and Shahar Mendelson* |

| | | **Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities** - *Peter Sollich* |

| | | **Lower bounds for the rate of convergence in nonparametric pattern recognition** - *Andràs Antos* |

| | | **Neural circuits for pattern recognition with small total wire length** - *Robert A. Legenstein and Wolfgang Maass* |

| | | **The Consistency Dimension and Distribution-Dependendent Learning from Queries** - *José L. Balcázar, Jorge Castro, David Guijarro and Hans-Ulrich Simon* |

| | | **15th Annual Conference on Computational Learning Theory, COLT 2002, Sydney, Australia, July 2002, Proceedings** - *Jyrki Kivinen and Robert H. Sloan* |

| | | **Reinforcement Learning for Call Admission Control and Routing under Quality of Service Constraints in Multimedia Networks** - *Hui Tong and Timothy X. Brown* |

| | | **Ordered Term Tree Languages which Are Polynomial Time Inductively Inferable from Positive Data** - *Yusuke Suzuki, Takayoshi Shoudai, Tomoyuki Uchida and Tetsuhiro Miyahara* |

| | | **Linear Programming Boosting via Column Generation** - *Ayhan Demiriz, Kristin P. Bennett and John Shawe-Taylor* |

| | | **Mathematics Based on Learning** - *Susumu Hayashi* |

| | | **Predictive Complexity and Information** - *Michael V. Vyugin and Vladimir V. V'yugin* |

| | | **Feasible Direction Decomposition Algorithms for Training Support Vector Machines** - *Pavel Laskov* |

| | | **RBF Neural Networks and Descartes' Rule of Signs** - *Michael Schmitt* |

| | | **Constraint Classification: A New Approach to Multiclass Classification** - *Sariel Har-Peled, Dan Roth and Dav Zimak* |

| | | **Avoiding coding tricks by hyperrobust learning** - *Matthias Ott and Frank Stephan* |

| | | **On the Power of Incremental Learning** - *Steffen Lange and Gunter Grieser* |

| | | **Technical Update: Least-Squares Temporal Difference Learning** - *Justin A. Boyan* |

| | | **On the Learnability and Design of Output Codes for Multiclass Problems** - *Koby Crammer and Yoram Singer* |

| | | **Prediction algorithms and confidence measures based on algorithmic randomness theory** - *Alex Gammerman and Volodya Vovk* |

| | | **Predicting Nearly as Well as the Best Pruning Graph** - *Eiji Takimoto and Manfred K. Warmuth* |

| | | **An Analytic Center Machine** - *Theodore B. Trafalis and Alexander M. Malyscheff* |

| | | **On the Existence of Linear Weak Learners and Applications to Boosting** - *Shie Mannor and Ron Meir* |

| | | **Boosting Methods for Regression** - *Nigel Duffy and David Helmbold* |

| | | **A Pathology of Bottom-Up Hill-Climbing in Inductive Rule Learning** - *Johannes Fürnkranz* |

| | | **Mixability and the Existence of Weak Complexities** - *Yuri Kalnishkan and Michael V. Vyugin* |

| | | **Path Kernels and Multiplicative Updates** - *Eiji Takimoto and Manfred K. Warmuth* |

| | | **Text Categorization with Support Vector Machines. How to Represent Texts in Input Space?** - *Edda Leopold and Jörg Kindermann* |

| | | **On the Proper Learning of Axis Parallel Concepts** - *Nader H. Bshouty and Lynn Burroughs* |

| | | **Logistic Regression, AdaBoost and Bregman Distances** - *Michael Collins, Robert E. Schapire and Yoram Singer* |

| | | **Some Local Measures of Complexity of Convex Hulls and Generalization Bounds** - *Olivier Bousquet, Vladimir Koltchinskii and Dmitriy Panchenko* |

| | | **Continuous-Action Q-Learning** - *José del R. Millán, Daniele Posenato and Eric Dedieu* |

| | | **On the Learnability of Vector Spaces** - *Valentina S. Harizanov and Frank Stephan* |

| | | **On the rate of convergence of error estimates for the partitioning classification rule** - *Márta Pintér* |

| | | **Guest Editor's Introduction** - *Jyrki Kivinen* |

| | | **Choosing Multiple Parameters for Support Vector Machines** - *Olivier Chapelle, Vladimir Vapnik, Olivier Bousquet and Sayan Mukherjee* |

| | | **Minimised Residue Hypotheses in Relevant Logic** - *Bertram Fronhöfer and Akihiro Yamamoto* |

| | | **Decision Region Connectivity Analysis: A Method for Analyzing High-Dimensional Classifiers** - *Ofer Melnik* |

| | | **Efficient SVM Regression Training with SMO** - *Gary William Flake and Steve Lawrence* |

| | | **Kernel-Based Reinforcement Learning** - *Dirk Ormoneit and Saunak Sen* |

| | | **Data Mining with Graphical Models** - *Rudolf Kruse and Christian Borgelt* |

| | | **Structure in the Space of Value Functions** - *David Foster and Peter Dayan* |

| | | **Category, Measure, Inductive Inference: A Triality Theorem and Its Applications** - *Rusins Freivalds and Carl H. Smith* |

| | | **Inferring Deterministic Linear Languages** - *Colin de la Higuera and Jose Oncina* |

| | | **Kernel Matching Pursuit** - *Pascal Vincent and Yoshua Bengio* |

| | | **Classification with Intersecting Rules** - *Tony Lindgren and Henrik Boström* |

| | | **A Simple Decomposition Method for Support Vector Machines** - *Chih-Wei Hsu and Chih-Jen Lin* |

| | | **Introduction** - *Satinder Singh* |

| | | **The Complexity of Learning Concept Classes with Polynomial General Dimension** - *Johannes Köbler and Wolfgang Lindner* |

| | | **Structural Modelling with Sparse Kernels** - *S. R. Gunn and J. S. Kandola* |

| | | **Learning, Logic, and Topology in a Common Framework** - *Eric Martin, Arun Sharma and Frank Stephan* |

| | | **Control structures in hypothesis spaces: the influence on learning** - *John Case, Sanjay Jain and Mandayam Suraj* |

| | | **Gene Selection for Cancer Classification using Support Vector Machines** - *Isabelle Guyon, Jason Weston, Stephen Barnhill and Vladimir Vapnik* |

| | | **Bayesian Clustering by Dynamics** - *Marco Ramoni, Paola Sebastiani and Paul Cohen* |

| | | **On Learning Embedded Midbit Functions** - *Rocco A. Servedio* |

| | | **Automata techniques for query inference machines** - *William Gasarch and Geoffrey R. Hird* |

| | | **Finite-time Analysis of the Multiarmed Bandit Problem** - *Peter Auer, Nicolò Cesa-Bianchi and Paul Fischer* |

| | | **Self-Optimizing and Pareto-Optimal Policies in General Environments Based on Bayes-Mixtures** - *Marcus Hutter* |

| | | **The Lagging Anchor Algorithm: Reinforcement Learning in Two-Player Zero-Sum Games with Imperfect Information** - *Fredrik A. Dahl* |

| | | **A Consistent Strategy for Boosting Algorithms** - *Gábor Lugosi and Nicolas Vayatis* |

| | | **A Simple Method for Generating Additive Clustering Models with Limited Complexity** - *Michael D. Lee* |

| | | **An Efficient PAC Algorithm for Reconstructing a Mixture of Lines** - *Sanjoy Dasgupta, Elan Pavlov and Yoram Singer* |

| | | **In Search of the Horowitz Factor: Interim Report on a Musical Discovery Project** - *Gerhard Widmer* |

| | | **Maximizing the Margin with Boosting** - *Gunnar Rätsch and Manfred K. Warmuth* |

| | | **Agnostic Learning Nonconvex Function Classes** - *Shahar Mendelson and Robert C. Williamson* |

| | | **Editorial** - *Doug Fisher* |

| | | **Prediction and Dimension** - *Lance Fortnow and Jack H. Lutz* |

| | | **New Lower Bounds for Statistical Query Learning** - *Ke Yang* |

| | | **A New Nonparametric Pairwise Clustering Algorithm Based on Iterative Estimation of Distance Profiles** - *Shlomo Dubnov, Ran El-Yaniv, Yoram Gdalyahu, Elad Schneidman, Naftali Tishby and Golan Yona* |

| | | **PAC Learning with Nasty Noise** - *Nader H. Bshouty, Nadav Eiron and Eyal Kushilevitz* |

| | | **Risk-Sensitive Reinforcement Learning** - *Oliver Mihatsch and Ralph Neuneier* |

| | | **Direct and indirect algorithms for on-line learning of disjunctions** - *D. P. Helmbold, S. Panizza and M. K. Warmuth* |

| | | **Polynomial Time Inductive Inference of Ordered Tree Patterns with Internal Structured Variables from Positive Data** - *Yusuke Suzuki, Ryuta Akanuma, Takayoshi Shoudai, Tetsuhiro Miyahara and Tomoyuki Uchida* |

| | | **Maximum Likelihood Estimation of Mixture Densities for Binned and Truncated Multivariate Data** - *Igor V. Cadez, Padhraic Smyth, Geoff J. McLachlan and Christine E. McLaren* |

| | | **Mind change complexity of learning logic programs** - *Sanjay Jain and Arun Sharma* |

| | | **Large Margin Classification for Moving Targets** - *Jyrki Kivinen, Alex J. Smola and Robert C. Williamson* |

| | | **Support Vector Machines for Classification in Nonstandard Situations** - *Yi Lin, Yoonkyung Lee and Grace Wahba* |

| | | **Learnability and Definability in Trees and Similar Structures** - *Martin Grohe and Gyorgy Turán* |

| | | **Sparse Regression Ensembles in Infinite and Finite Hypothesis Spaces** - *Gunnar Rätsch, Ayhan Demiriz and Kristin P. Bennett* |

| | | **A Negative Result on Inductive Inference of Extended Pattern Languages** - *Daniel Reidenbach* |

| | | **Learning Structure from Sequences, with Applications in a Digital Library** - *Ian H. Witten* |

| | | **Statistical Properties and Adaptive Tuning of Support Vector Machines** - *Yi Lin, Grace Wahba, Hao Zhang and Yoonkyung Lee* |

| | | **PAC Bounds for Multi-armed Bandit and Markov Decision Processes** - *Eyal Even-Dar, Shie Mannor and Yishay Mansour* |

| | | **Large Scale Kernel Regression via Linear Programming** - *.L. Mangasarian and David R. Musicant* |

| | | **Guest Introduction: Special Issue on New Methods for Model Selection and Model Combination** - *Yoshua Bengio and Dale Schuurmans* |

| | | **Model Selection and Error Estimation** - *Peter L. Bartlett, Stéphane Boucheron and Gáabor Lugosi* |

| | | **A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes** - *Michael Kearns, Yishay Mansour and Andrew Y. Ng* |

| | | **The Relaxed Online Maximum Margin Algorithm** - *Yi Li and Philip M. Long* |

| | | **Hierarchical Learning in Polynomial Support Vector Machines** - *Sebastian Risau-Gusman and Mirta B. Gordon* |

| | | **On Learning Unions of Pattern Languages and Tree Patterns in the Mistake Bound Model** - *Sally A. Goldman and Stephen S. Kwek* |

| | | **Bayesian Treed Models** - *Hugh A. Chipman, Edward I. George and Robert E. McCulloch* |

| | | **Exploring Learnability between Exact and PAC** - *Nader H. Bshouty, Jeffrey C. Jackson and Christino Tamon* |

| | | **Learning Classes of Approximations to Non-Recursive Functions** - *Frank Stephan and Thomas Zeugmann* |

| | | **A geometric approach to leveraging weak learners** - *Nigel Duffy and David Helmbold* |

| | | **Geometric Parameters of Kernel Machines** - *Shahar Mendelson* |

| | | **Convergence of a Generalized SMO Algorithm for SVM Classifier Design** - *S. S. Keerthi and E. G. Gilbert* |

| | | **Optimally-Smooth Adaptive Boosting and Application to Agnostic Learning** - *Dmitry Gavinsky* |

| | | **On Average Versus Discounted Reward Temporal-Difference Learning** - *John N. Tsitsiklis and Benjamin Van Roy* |

| | | **Preface** - *Osamu Watanabe and Arun Sharma* |

| | | **How Many Missing Answers Can Be Tolerated by Query Learners?** - *Hans Ulrich Simon* |

| | | **Theory Revision with Queries: DNF Formulas** - *Judy Goldsmith, Robert H. Sloan and György Turán* |

| November | | **Algorithmic Learning Theory, 13th International Conference, ALT 2002, Lübeck, Germany, November 2002, Proceedings** - *Nicolò Cesa-Bianchi and Masayuki Numao and Rüdiger Reischuk* |

Circ | _textmontha _ | | **Quodlibeta Septem (in translation)** - *William of Occam* |