2000 | | | **Learning Trading Rules with Inductive Logic Programming** - *Liviu Badea* |

| | | **Complete Cross-Validatin for Nearest Neighbor Classifiers** - *Matthew Mullin and Rahul Sukthankar* |

| | | **Feature Selection vs Theory Reformulation: A Study of Genetic Refinement of Knowledge-based Neural Networks** - *Brendan Davis Burns and Andrea Pohoreckyj-Danyluk* |

| | | **Solving the Multiple-Instance Problem: A Lazy Learning Approach** - *Jun Wang and Jean-Daniel Zucker* |

| | | **Resource-Bounded Measure and Learnability** - *W. Lindner, R. Schuler and O. Watanabe* |

| | | **Technical Note: Naive Bayes for Regression** - *Eibe Frank, Leonard Trigg, Geoffrey Holmes and Ian H. Witten* |

| | | **Machine Learning: ECML 2000, 11th European Conference on Machine Learning, Barcelona, Catalonia, Spain, May 31 - June 2, 2000, Proceedings** - *Ramon López de Mántaras and Enric Plaza* |

| | | **Bounds on the Generalization Performance of Kernel Machine Ensembles** - *Theodoros Evgeniou, Luis Perez-Breva, Massimiliano Pontil and Tomaso Poggio* |

| | | **A Cognitive Bias Approach to Feature Selection and Weighting for Case-Based Learners** - *Claire Cardie* |

| | | **Inductive inference of unbounded unions of pattern languages from positive data** - *Takeshi Shinohara and Hiroki Arimura* |

| | | **Computational Complexity of Problems on Probabilistic Grammars and Transducers** - *F. Casacuberta and Colin De La Higuera* |

| | | **Asymmetric Co-evolution for Imperfect-Information Zero-Sum Games** - *Ole Martin Halck and Fredrik A. Dahl* |

| | | **Using Error-Correcting Codes for Text Classification** - *Rayid Ghani* |

| | | **An Integrated Connectionist Approach to Reinforcement Learning for Robotic Control: The Advantages of Indexed Partitioning** - *Dean F. Hougen, Maria Gini and James Slagle* |

| | | **An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods** - *Nello Cristianini and John Shawe-Taylor* |

| | | **Learning Subjective Functions with Large Margins** - *Claude-Nicolas Fiechter and Seth Rogers* |

| | | **Multi-Agent Reinforcement Learning for Traffic Light Control** - *Marco Wiering* |

| | | **Convergence Results for Single-Step On-Policy Reinforcement-Learning Algorithms** - *Satinder Singh, Tommi Jaakkola, Michael L. Littman and Csaba Szepesvári* |

| | | **Hidden Strengths and Limitations: An Empirical Investigation of Reinforcement Learning** - *Gerald DeJong* |

| | | **A Universal Generalization for Temporal-Difference Learning Using Haar Basis Functions** - *Susumu Katayama, Hajime Kimura and Shigenobu Kobayashi* |

| | | **Query Learning with Large Margin Classifiers** - *Colin Campbell, Nello Cristianini and Alex Smola* |

| | | **Bootstrapping Syntax and Recursion using Alignment-Based Learning** - *Menno van Zaanen* |

| | | **Robot Navigation with Distance Queries** - *Dana Angluin, Jeffery Westbrook and Wenhong Zhu* |

| | | **Crafting Papers on Machine Learning** - *Pat Langley* |

| | | **Mutual Information in Learning Feature Transformations** - *Kari Torkkola and William M. Campbell* |

| | | **Clustering with Instance-level Constraints** - *Kiri Wagstaff and Claire Cardie* |

| | | **Efficient Learning Trough Evolution: Neural Programming and Internal Reinforcement** - *Astro Teller and Manuela Veloso* |

| | | **Algorithms for Inverse Reinforcement Learning** - *Andrew Y. Ng and Stuart Russell* |

| | | **PAC Analogues of Perceptron and Winnow via Boosting the Margin** - *Rocco A. Servedio* |

| | | **On inferring linear single-tree languages** - *Erkki Mäkinen* |

| | | **Query learning of bounded-width OBDDs** - *Atsuyoshi Nakamura* |

| | | **Learning Monotone Log-Term DNF Formulas under the Uniform Distribution** - *Y. Sakai and A. Maruoka* |

| | | **Efficient Ambiguity Detection in C-NFA, a Step Towards the Inference on Non Deterministic Automata** - *François Coste and Daniel Fredouille* |

| | | **Improve the Learning of Subsequential Transducers by Using Alignments and Dictionaries** - *Juan Miguel Vilar* |

| | | **Linear Discriminant Trees** - *Olcay Taner Yildiz and Ethem Alpaydin* |

| | | **An Evolutionary Approach to Evidence-Based Learning of Deterministic Finite Automata** - *Stefan Veeser* |

| | | **Exploiting the Cost of (In)sensitivity of Decision Tree Splitting Criteria** - *Chris Drummond and Robert C. Holte* |

| | | **The Precision of Query Points as a Resource for Learning Convex Polytopes with Membership Queries** - *Paul Goldberg and Stephen Kwek* |

| | | **A Comparative Study of Two Algorithms for Automata Identification** - *Pedro Garcia, A. Cano and José Ruiz* |

| | | **Version Space Algebra and its Application to Programming by Demonstration** - *Tessa Lau, Pedro Domingos and Daniel S. Weld* |

| | | **A Boosting Approach to Topic Spotting on Subdialogues** - *Kary Myers, Michael Kearns, Satinder Singh and Marilyn A. Walker* |

| | | **Exploiting Classifier Combination for Early Melanoma Diagnosis Support** - *Enrico Blanzieri, C. Eccher, S. Forti and A. Sboner* |

| | | **"Boosting" a Positive-Data-Only Learner** - *Andrew Mitchell* |

| | | **Investigation and Reduction of Discretization Variance in Decision Tree Induction** - *Pierre Geurts and Louis Wehenkel* |

| | | **Average-Case Analysis of Classification Algorithms for Boolean Functions and Decision Trees** - *Tobias Scheffer* |

| | | **Discovery Science, Third International Conference, DS 2000, Kyoto, Japan, December 2000, Proceedings** - *Setsuo Arikawa and Shinichi Morishita* |

| | | **An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees: Bagging, Boosting, and Randomization** - *Thomas G. Dietterich* |

| | | **Eligibility Traces for Off-Policy Policy Evaluation** - *Doina Precup, Richard S. Sutton and Satinder Singh* |

| | | **MultiStage Cascading of Multiple Classifiers: One Man's Noise is Another Man's Data** - *Cenk Kaynak and Ethem Alpaydin* |

| | | **Structural measures for games and process control in the branch learning model** - *Matthias Ott and Frank Stephan* |

| | | **Discovery and Deduction** - *Masami Hagiya and Koichi Takahashi* |

| | | **The learnability of exclusive-or expansions based on monotone DNF formulas** - *Eiji Takimoto, Yoshifumi Sakai and Akira Maruoka* |

| | | **Synthesizing Context Free Grammars from Sample Strings Based on Inductive CYK Algorithm** - *Katsuhiko Nakamura and Takashi Ishiwata* |

| | | **A Polynomial Time Approximation Scheme for Inferring Evolutionary Trees from Quartet Topologies and Its Application** - *Tao Jiang, Paul Kearney and Ming Li* |

| | | **Minimum Message Length Grouping of Ordered Data** - *Leigh J. Fitzgibbon, Lloyd Allison and David L. Dowe* |

| | | **Constructive Feature Learning and the Development of Visual Expertise** - *Justus H. Piater and Roderic A. Grupen* |

| | | **Stochastic Grammatical Inference of Text Database Structure** - *Matthew Young-Lai and Frank WM. Tompa* |

| | | **Predicting the Generalization Performance of Cross Validatory Model Selection Criteria** - *Tobias Scheffer* |

| | | **Cascade Generalization** - *João Gama and Pavel Brazdil* |

| | | **Identification of Tree Translation Rules from Examples** - *Hiroshi Sakamoto, Hiroki Arimura and Setsuo Arikawa* |

| | | **Extracting Information from the Web for Concept Learning and Collaborative Filtering** - *William W. Cohen* |

| | | **Improving Short-Text Classification Using Unlabeled Background Knowledge to Assess Document Similarity** - *Sarah Zelikovitz and Haym Hirsh* |

| | | **Enlarging the Margins in Perceptron Decision Trees** - *Kristin P. Bennett, Nello Cristianini, John Shawe-Taylor and Donghui Wu* |

| | | **On the Difficulty of Approximately Maximizing Agreements** - *Shai Ben-David, Nadav Eiron and Philip M. Long* |

| | | **Strategies in Combined Learning via Logic Programs** - *E. Lamma, F. Riguzzi and L. M. Pereira* |

| | | **Obtaining Simplified Rule Bases by Hybrid Learning** - *Ricardo Bezerra de Andrade e Silva and Teresa Bernarda Ludermir* |

| | | **A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirty-Three Old and New Classification Algorithms** - *Tjen-Sien Lim, Wei-Yin Loh and Yu-Shan Shih* |

| | | **Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning** - *Mark A. Hall* |

| | | **Computationally Efficient Transductive Machines** - *Craig Saunders, Alexander Gammerman and Volodya Vovk* |

| | | **Implementation Issues in the Fourier Transform Algorithm** - *Yishay Mansour and Sigal Sahar* |

| | | **Learning to Predict Performance from Formula Modeling and Training Data** - *Bryan Singer and Manuela Veloso* |

| | | **Improved Algorithms for Theory Revision with Queries** - *Judy Goldsmith, Robert H. Sloan, B. Szörényi and G. Turán* |

| | | **Anomaly Detection over Noisy Data using Learned Probability Distributions** - *Eleazar Eskin* |

| | | **Boosting Applied toe Word Sense Disambiguation** - *Gerard Escudero, Lluís Màrquez and German Rigau* |

| | | **Discovering Test Set Regularities in Relational Domains** - *Seán Slattery and Tom Mitchell* |

| | | **A Multistrategy Approach to Classifier Learning from Time Series** - *William H. Hsu, Sylvian R. Ray and David C. Wilkins* |

| | | **Multistrategy Theory Revision: Induction and Abduction in INTHELEX** - *Floriana Esposito, Giovanni Semeraro, Nicola Fanizzi and Stefano Ferilli* |

| | | **Detecting Concept Drift with Support Vector Machines** - *Ralf Klinkenberg and Thorsten Joachims* |

| | | **Minimax TD-Learning with Neural Nets in a Markov Game** - *Fredrik A. Dahl and Ole Martin Halck* |

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

| | | **Resource-bounded Relational Reasoning: Induction and Deduction Through Stochastic Matching** - *M. Sebag and C. Rouveirol* |

| | | **Dimension Reduction Techniques for Training Polynomial Networks** - *William M. Campbell, Kari Torkkola and Sreeram V. Balakrishnan* |

| | | **Learning Multiple Models for Reward Maximization** - *Dani Goldberg and Maja J. Matarić* |

| | | **Using Natural Language Processing and Discourse Features to Identify Understanding Errors in a Spoken Dialogue System** - *Marilyn Walker, Jerry Wright and Irene Langkilde* |

| | | **Continuous Drifting Games** - *Yoav Freund and Manfred Opper* |

| | | **Measuring Performance when Positives Are Rare: Relative Advantage versus Predictive Accuracy - A Biological Case Study** - *Stephen Muggleton, Christopher H. Bryant and Ashwin Srinivasan* |

| | | **Learning Priorities from Noisy Examples** - *Geoffrey G. Towell, Thomas Petsche and Michael R. Miller* |

| | | **On the Hardness of Learning Acyclic Conjunctive Queries** - *Kouichi Hirata* |

| | | **Wrapper Generation via Grammar Induction** - *Boris Chidlovskii, Jon Ragetli and Maarten de Rijke* |

| | | **The Divide-and-Conquer Manifesto** - *Thomas G. Dietterich* |

| | | **Machine Learning of Event Segmentation for News on Demand** - *Stanley Boykin and Andrew Merlino* |

| | | **A Simple Greedy Algorithm for Finding Functional Relations: Efficient Implementation and Average Case Analysis** - *Tatsuya Akutsu, Satoru Miyano and Satoru Kuhara* |

| | | **Lazy Learning of Bayesian Rules** - *Zijian Zheng and Geoffrey I. Webb* |

| | | **Learning to Create Customized Authority Lists** - *Huan Chang, David Cohn and Andrew K. McCallum* |

| | | **Parallel Attribute-Efficient Learning of Monotone Boolean Functions** - *Peter Damaschke* |

| | | **Language Learning From Texts: Degrees of Instrinsic Complexity and Their Characterizations** - *Sanjay Jain, Efim Kinber and Rolf Wiehagen* |

| | | **An Approach to Data Reduction and Clustering with Theoretical Guarantees** - *Partha Niyogi and Narendra Karmarkar* |

| | | **Disciple-COA: From Agent Programming to Agent Teaching** - *Mihai Boicu, Gheorghe Tecuci, Dorin Marcu, Michael Bowman, Ping Shyr, Florin Ciucu and Cristian Levcovici* |

| | | **A Multiple Model Cost-Sensitive Approach for Intrusion Detection** - *Wei Fan, Wenke Lee, Salvatore J. Stolfo and Matthew Miller* |

| | | **Automatically Extracting Features for Concept Learning from the Web** - *William W. Cohen* |

| | | **An Initial Study of an Adaptive Hierarchical Vision System** - *Marcus A. Maloof* |

| | | **Some classes of prolog programs inferable from positive data** - *M. R. K. Krishna Rao* |

| | | **Direct Bayes Point Machines** - *Matthias Rychetsky, John Shawe-Taylor and Manfred Glesner* |

| | | **Value Miner: A Data Mining Environment for the Calculation of the Customer Lifetime Value with Application to the Automotive Industry** - *Katja Gelbrich and Reza Nakhaeizadeh* |

| | | **A Column Generation Algorithm for Boosting** - *Kristin P. Bennett, Ayhan Demiriz and John Shawe-Taylor* |

| | | **Permutations and Control Sets for Learning Non-regular Language Families** - *Henning Fernau and Jose M. Sempere:* |

| | | **State-based Classification of Finger Gestures from Electromyographic Signals** - *Peter Ju, Leslie Pack Kaelbling and Yoram Singer* |

| | | **Rates of Convergence for Variable Resolution Schemes in Optimal Control** - *Rémi Munos and Andrew W. Moore* |

| | | **Local Expert Autoassociators for Anomaly Detection** - *Geoffrey G. Towell* |

| | | **Dynamic Hand Gesture Recognition Based on Randomized Self-Organizing Map Algorithm** - *Tarek El. Tobely, Yuichiro Yoshiki, Ryuichi Tsuda, Naoyuki Tsuruta and Makoto Amamiya* |

| | | **A Unifying Approach to HTML Wrapper Representation and Learning** - *Gunter Grieser, Klaus P. Jantke, Steffen Lange and Bernd Thomas* |

| | | **Polynomial Time Learnability of Simple Deterministic Languages from MAT and a Representative Sample** - *Yasuhiro Tajima, Etsuji Tomita and Mitsuo Wakatsuki* |

| | | **Combining Multiple Perspectives** - *Bikramjit Banerjee, Sandip Debnath and Sandip Sen* |

| | | **Less is More: Active Learning with Support Vector Machines** - *Greg Schohn and David Cohn* |

| | | **Meta-Learning by Landmarking Various Learning Algorithms** - *Bernhard Pfahringer, Hilan Bensusan and Christophe Giraud-Carrier* |

| | | **Text Classification from Labeled and Unlabeled Documents using EM** - *Kamal Nigam, Andrew Kachites Mccallum, Sebastian Thrun and Tom Mitchell* |

| | | **Model Selection Criteria for Learning Belief Nets: An Empirical Comparison** - *Tim Van Allen and Russ Greiner* |

| | | **Finding Variational Structure in Data by Cross-Entropy Optimization** - *Matthew Brand* |

| | | **Efficient Mining from Large Database by Query Learning** - *Hiroshi Mamitsuka and Naoki Abe* |

| | | **A Bayesian Approach to Temporal Data Clustering using Hidden Markov Models** - *Cen Li and Gautam Biswas* |

| | | **Characterizing Model Errors and Differences** - *Stephen D. Bay and Michael J. Pazzani* |

| | | **Self-Duality of Bounded Monotone Boolean Functions and Related Problems** - *Daya Ram Gaur and Ramesh Krishnamurti* |

| | | **Identification in the Limit with Probability One of Stochastic Deterministic Finite Automata** - *Colin De La Higuera and Franck Thollard* |

| | | **Comparing Complete and Partial Classification for Identifying Latently Dissatisfied Customers** - *Tom Brijs, Gilbert Swinnen, Koen Vanhoof and Geert Wets* |

| | | **Challenges of the Email Domain for Text Classification** - *Jake D. Brutlag and Christopher Meek* |

| | | **Discovering the Structure of Partial Differential Equations from Example Behavior** - *Ljupčo Todorovski, Sašo Džeroski, Ashwin Srinivasan, Jonathan Whiteley and David Gavaghan* |

| | | **Sparsity vs. Large Margins for Linear Classifiers** - *Ralf Herbrich, Thore Graepel and John Shawe-Taylor* |

| | | **Generalisation Error Bounds for Sparse Linear Classifiers** - *Thore Graepel, Ralf Herbrich and John Shawe-Taylor* |

| | | **Relative Loss Bounds for Temporal-Difference Learning** - *Jürgen Forster and Manfred Warmuth* |

| | | **Exact learning via teaching assistants** - *V. Arvind and N. V. Vinodchandran* |

| | | **Proceedings of the Thirteenth Annual Conference on Computational Learning Theory** - *N. Cesa-Bianchi and S. Goldman* |

| | | **A Dynamic Adaptation of AD-trees for Efficient Machine Learning on Large Data Sets** - *Paul Komarek and Andrew Moore* |

| | | **BoosTexter: A Boosting-based System for Text Categorization** - *Robert E. Schapire and Yoram Singer* |

| | | **Inference of Finite-State Transducers by Using Regular Grammars and Morphisms** - *F. Casacuberta* |

| | | **On the Convergence Rate of Good-Turing Estimators** - *David McAllester and Robert E. Schapire* |

| | | **Selective Voting for Perceptron-like Online Learning** - *Yi Li* |

| | | **Multiple Comparisons in Induction Algorithms** - *David D. Jensen and Paul R. Cohen* |

| | | **Locally Weighted Projection Regression: An O(n) Algorithm for Incremental Real Time Learning in High Dimensional Space** - *Sethu Vijayakumar and Stefan Schaal* |

| | | **Learning Context-Free Grammars from Partially Structured Examples** - *Yasubumi Sakakibara and Hidenori Muramatsu* |

| | | **Decision Tree Approximations of Boolean Functions** - *Dinesh Mehta and Vijay Raghavan* |

| | | **Knowledge Propagation in Model-based Reinforcement Learning Tasks** - *Corinna Richter and Jörg Stachowiak* |

| | | **Mixtures of Factor Analyzers** - *Geoffrey McLachlan* |

| | | **Analyzing Relational Learning in the Phase Transition Framework** - *Attilio Giordana, Lorenza Saitta, Michele Sebag and Marco Botta* |

| | | **Multi Level Knowledge in Modeling Qualitative Physics Learning** - *Filippo Neri* |

| | | **Leveraging for Regression** - *Nigel Duffy and David Helmbold* |

| | | **How rich is the structure of the intrinsic complexity of learning** - *Andris Ambainis* |

| | | **Using Upper Confidence Bounds for Online Learning** - *Peter Auer* |

| | | **Learning Recursive Concepts with Anomalies** - *Gunter Grieser, Steffen Lange and Thomas Zeugmann* |

| | | **On-line Learning for Humanoid Robot Systems** - *Jörg Conradt, Gaurav Tevatia, Sethu Vijayakumar and Stefan Schaal* |

| | | **Team Learning of Computable Languages** - *Sanjay Jain and Arun Sharma* |

| | | **A Quantification of Distance-Bias Between Evaluation Metrics In Classification** - *Ricardo Vilalta and Daniel Oblinger* |

| | | **Probabilistic k-Testable Tree Languages** - *Juan Ramón Rico-Juan, Jorge Calera-Rubio and Rafael C. Carrasco* |

| | | **Error Analysis of Automatic Speech Recognition Using Principal Direction Divisive Partitioning** - *David McKoskey and Daniel Boley* |

| | | **A Polynomial Time Learning Algorithm Simple Deterministic Languages via Membership Queries and a Representative Sample** - *Yasuhiro Tajima and Etsuji Tomita* |

| | | **Testing of Clustering** - *Noga Alon, Seannie Dar, Michal Parnas and Dana Ron* |

| | | **Why Discretization Works for Na\"ıve Bayesian Classifiers** - *Chun-Nan Hsu, Hung-Ju Huang and Tzu-Tsung Wong* |

| | | **Reduction Techniques for Instance-Based Learning Algorithms** - *D. Randall Wilson and Tony R. Martinez* |

| | | **Adaptive and Self-Confident On-Line Learning Algorithms** - *Peter Auer and Claudio Gentile* |

| | | **Fixed Points of Approximate Value Iteration and Temporal-Difference Learning** - *Daniela Pucci de Farias and Benjamin Van Roy* |

| | | **Statistical Sufficiency for Classes in Empirical L**_{2} Spaces - *Shahar Mendelson and Naftali Tishby* |

| | | **Unpacking Multi-valued Symbolic Features and Classes in Memory-based Language Learning** - *Antal van den Bosch and Jakub Zavrel* |

| | | **Automatic Identification of Mathematical Concepts** - *Simon Colton, Alan Bundy and Toby Walsh* |

| | | **Layered Learning** - *Peter Stone and Manuela M. Veloso* |

| | | **Computation of Substring Probabilities in Stochastic Grammars** - *Ana L. N. Fred* |

| | | **Data as Ensembles of Records: Representation and Comparison** - *Nicholas R. Howe* |

| | | **Vacillatory and BC learning on noisy data** - *John Case, Sanjay Jain and Frank Stephan* |

| | | **Discriminative Reranking for Natural Language Parsing** - *Michael Collins* |

| | | **Acquisition of Stand-up Behavior by a Real Robot using Hierarchical Reinforcement Learning** - *Jun Morimoto and Kenji Doya* |

| | | **Distribution-balanced stratified cross-validation for accuracy estimation** - *Xinchuan Zeng and Tony R. Martinez* |

| | | **LEARNABLE EVOLUTION MODEL: Evolutionary Processes Guided by Machine Learning** - *Ryszard S. Michalski* |

| | | **An Efficient and Effective Procedure for Updating a Competence Model for Case-Based Reasoner** - *Barry Smyth and Elizabeth McKenna* |

| | | **Incremental Learning in SwiftFile** - *Richard B. Segal and Jeffrey O. Kephart* |

| | | **Comparing the Minimum Description Length Principle and Boosting in the Automatic Analysis of Discourse** - *Tadashi Nomoto and Yuji Matsumoto* |

| | | **Combining multiple learning strategies for effective cross validation** - *Yiming Yang, Thomas Ault and Thomas Pierce* |

| | | **A discipline of evolutionary programming** - *Paul Vitányi* |

| | | **Complexity Approximation Principle and Rissanen's Approach to Real-Valued Parameters** - *Yuri Kalnishkan* |

| | | **Computational Sample Complexity and Attribute-Efficient Learning** - *Rocco A. Servedio* |

| | | **Learning functions represented as multiplicity automata** - *Amos Beimel, Francesco Bergadano, Nader H. Bshouty, Eyal Kushilevitz and Stefano Varricchio* |

| | | **Entropy Numbers of Linear Function Classes** - *Robert C. Williamson, Alex J. Smola and Bernhard Schölkopf* |

| | | **The Space of Jumping Emerging Patterns and Its Incremental Maintenance Algorithms** - *Jinyan Li and Kotagiri Ramamohanarao* |

| | | **Counting Extensional Differences in BC-Learning** - *Frank Stephan and Sebastiaan A. Terwijn* |

| | | **On the Relationship between Models for Learning in Helpful Environments** - *Rajesh Parekh and Vasant Honavar* |

| | | **More theory revision with queries (extended abstract)** - *Judy Goldsmith and Robert H. Sloan* |

| | | **Achieving Efficient and Congnitively Plausible Learning in Backgammon** - *Scott Sanner, John R. Anderson, Christian Lebiere and Marsha Lovett* |

| | | **A Nonparametric Approach to Noisy and Costly Optimization** - *Brigham S. Anderson, Andrew W. Moore and David Cohn* |

| | | **Dynamic Discretization of Continuous Values from Time Series** - *Llanos Mora López, Inmaculada Fortes Ruiz, Rafael Morales Bueno and Francisco Triguero Ruiz* |

| | | **Dynamic Feature Selection in Incremental Hierarchical Clustering** - *Luis Talavera* |

| | | **A Unified Bias-Variance Decomposition and its Applications** - *Pedro Domingos* |

| | | **Induction of Concept Hierarchies from Noisy Data** - *Blaž Zupan, Ivan Bratko, Marko Bohanec and Janez Demšar* |

| | | **Dimensionality Reduction through Sub-space Mapping for Nearest Neighbor Algorithms** - *Terry R. Payne and Peter Edwards* |

| | | **Smoothing Probabilistic Automata: An Error-Correcting Approach** - *Pierre Dupont and Juan-Carlos Amengual* |

| | | **A Probability Analysis on the Value of Unlabeled Data for Classification Problems** - *Tong Zhang and Frank J. Oles* |

| | | **Learning Declarative Control Rules for Constraint-Based Planning** - *Yi-Cheng Huang, Bart Selman and Henry Kautz* |

| | | **Learning Patterns of Behavior by Observing System Events** - *Marlon Núñez* |

| | | **PACS, simple-PAC and query learning** - *Jorge Castro and David Guijarro* |

| | | **Design Aspects of Discovery Systems** - *Osamu Maruyama and Satoru Miyano* |

| | | **Learning Taxonomic Relation by Case-Based Reasoning** - *Ken Satoh* |

| | | **Noise-tolerant learning, the parity problem, and the statistical query model** - *Avrim Blum, Adam Kalai and Hal Wasserman* |

| | | **Classification of Individuals with Complex Structure** - *A. F. Bowers, C. Giraud-Carrier and J. W. Lloyd* |

| | | **Enhancing Supervised Learning with Unlabeled Data** - *Sally Goldman and Yan Zhou* |

| | | **A Note on the Generalization Performance of Kernel Classifiers with Margin** - *Theodoros Evgeniou and Massimiliano Pontil* |

| | | **Editorial** - *Arun Sharma* |

| | | **Approximate Dimension Equalization in Vector-based Information Retrieval** - *Fan Jiang and Michael L. Littman* |

| | | **Metric-Based Inductive Learning Using Semantic Height Functions** - *Zdravko Markov and Ivo Marinchev* |

| | | **Language Learning with a Neighbor System** - *Yasuhito Mukouchi and Masako Sato* |

| | | **Experimental Results on Q-Learning for General-Sum Stochastic Games** - *Junling Hu and Michael P. Wellman* |

| | | **Computable Shell Decomposition Bounds** - *John Langford and David McAllester* |

| | | **Knowledge Representation Issues in Control Knowledge Learning** - *Ricardo Aler, Daniel Borrajo and Pedro Isasi* |

| | | **Selecting Examples for Partial Memory Learning** - *Marcus A. Maloof and Ryszard S. Michalski* |

| | | **Relative Unsupervised Discretization for Regression Problems** - *Marcus-Christopher Ludl and Gerhard Widmer* |

| | | **Behavioral Cloning of Student Pilots with Modular Neural Networks** - *Charles W. Anderson, Bruce A. Draper and David A. Peterson* |

| | | **Improving Algorithms for Boosting** - *Javed A. Aslam* |

| | | **Handling Continuous-Valued Attributes in Decision Tree with Neural Network Modelling** - *DaeEun Kim and Jaeho Lee* |

| | | **Improving Knowledge Discovery Using Domain Knowledge in Unsupervised Learning** - *Javier Béjar* |

| | | **Sequential Sampling Techniques for Algorithmic Learning Theory** - *Osamu Watanabe* |

| | | **K-SVRC. A Multi-class Support Vector Machine** - *Andreu Català Cecilio Angulo* |

| | | **Learning unions of high-dimensional boxes over the reals** - *Amos Beimel and Eyal Kushilevitz* |

| | | **Average-Case Complexity of Learning Polynomials** - *Frank Stephan and Thomas Zeugmann* |

| | | **Structural Results about Exact Learning with Unspecified Attribute Values** - *Andreas Birkendorf, Norbert Klasner, Christian Kuhlmann and Hans Ulrich Simon* |

| | | **Diversity versus Quality in Classification Ensembles Based on Feature Selection** - *Padraig Cunningham and John Carney* |

| | | **Voting Nearest-Neighbor Subclassifiers** - *Miroslav Kubat and Jr. Martin Cooperson* |

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

| | | **On Approximate Learning by Multi-layered Feedforward Circuits** - *Bhaskar DasGupta and Barbara Hammer* |

| | | **A Machine Learning Approach to POS Tagging** - *L. Màrquez, L. Padró and H. Rodriguez* |

| | | **Estimation and Approximation Bounds for Gradient-Based Reinforcement Learning** - *Peter L. Bartlett and Jonathan Baxter* |

| | | **Some Improvements on Event-Sequence Temporal Region Methods** - *Wei Zhang* |

| | | **Learning Distributed Representations by Mapping Concepts and Relations into a Linear Space** - *Alberto Paccanaro and Geoffrey E. Hinton* |

| | | **Sample Complexity of Model-Based Search** - *Christopher D. Rosin* |

| | | **TPOT-RL Applied to Network Routing** - *Peter Stone* |

| | | **P-sufficient statistics for PAC learning k-term-DNF formulas through enumeration** - *B. Apolloni and C. Gentile* |

| | | **Learning to Select Text Databases with Neural Nets** - *Yong S. Choi and Suk I. Yoo* |

| | | **Bayesian Averaging of Classifiers and the Overfitting Problem** - *Pedro Domingos* |

| | | **Learning Bayesian Networks for Diverse and Varying Numbers of Evidence Sets** - *Zu Whan Kim and Ramakant Nevatia* |

| | | **Problem Decomposition for Behavioural Cloning** - *Dorian Suc and Ivan Bratko* |

| | | **Constructive Learning of Context-Free Languages with a Subpansive Tree** - *Noriko Sugimoto, Takashi Toyoshima, Shinichi Shimozono and Kouichi Hirata* |

| | | **Upper and Lower Bounds on the Learning Curve for Gaussian Processes** - *Christopher K. I. Williams and Francesco Vivarelli* |

| | | **Discovering Homogeneous Regions in Spatial Data through Competition** - *Slobodan Vucetic and Zoran Obradovic* |

| | | **EM Algorithm with Split and Merge Operations for Mixture Models** - *Naonori Ueda and Ryohei Nakano* |

| | | **Enhancing the Plausibility of Law Equation Discovery** - *Takashi Washio, Hiroshi Motoda and Yuji Niwa* |

| | | **Estimating the Generalization Performance of an SVM Efficiently** - *Thorsten Joachims* |

| | | **Combining Reinforcement Learning with a Local Control Algorithm** - *Jette Randløv, Andrew G. Barto and Michael T. Rosenstein* |

| | | **Using Multiple Levels of Learning and Diverse Evidence Sources to Uncover Coordinately Controlled Genes** - *Mark Craven, David Page, Jude Shavlik, Joseph Bockhorst and Jeremy Glasner* |

| | | **Inductive Logic Programming: From Logic of Discovery to Machine Learning** - *Hiroki Arimura and Akihiro Yamamoto* |

| | | **Learing Horn Expressions with LogAn-H** - *Roni Khardon* |

| | | **Relative Expexted Instantaneous Loss Bounds** - *Jürgen Forster and Manfred Warmuth* |

| | | **The Degenerate Science of Machine Learning** - *Bat Gangly* |

| | | **Sharper Bounds for the Hardness of Prototype and Feature Selection** - *Richard Nock and Marc Sebban* |

| | | **On the Boosting Pruning Problem** - *Christino Tamon and Jie Xiang* |

| | | **Markov Processes on Curves** - *Lawrence K. Saul and Mazin G. Rahim* |

| | | **An Inverse Limit of Context-Free Grammars - A New Approach to Identifiability in the Limit** - *Pavel Martinek* |

| | | **On-line Learning and the Metrical Task System Problem** - *Avrim Blum and Carl Burch* |

| | | **Adaptive Resolution Model-Free Reinforcement Learning: Decision Boundary Partitioning** - *Stuart I. Reynolds* |

| | | **Mining TCP/IP Traffic for Network Intrusion Detection by Using a Distributed Genetic Algorithm** - *Filippo Neri* |

| | | **Machine Learning for Information Extraction in Informal Domains** - *Dayne Freitag* |

| | | **Learning to Play Chess Using Temporal Differences** - *Jonathan Baxter, Andrew Tridgell and Lex Weaver* |

| | | **Localizing Policy Gradient Estimates to Action Transitions** - *Gregory Z. Grudic and Lyle H. Ungar* |

| | | **Short-Term Profiling for a Case-Based Reasoning** - *Esma A\"ımeur and Mathieu Vézeau* |

| | | **Learning Erasing Pattern Languages with Queries** - *Jochen Nessel and Steffen Lange* |

| | | **Constructing X-of-N Attributes for Decision Tree Learning** - *Zijian Zheng* |

| | | **Iterated Transductions and Efficient Learning from Positive Data: A Unifying View** - *Satoshi Kobayashi* |

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

| | | **Adaptive Retrieval Agents: Internalizing Local Context and Scaling up to the Web** - *Filippo Menczer and Richard K. Belew* |

| | | **On the Noise Model of Support Vector Machines Regression** - *Massimiliano Pontil, Sayan Mukherjee and Federico Girosi* |

| | | **Feature Selection and Incremental Learning of Probabilistic Concept Hierarchies** - *Louis Talavera* |

| | | **The Representation Race - Preprocessing for Handling Time Phenomena** - *Katharina Morik* |

| | | **Ideal Theory Refinement under Object Identity** - *Floriana Esposito, Nicola Fanizzi, Stefano Ferilli and Giovanni Semeraro* |

| | | **Selection of Support Vector Kernel Parameters for Improved Generalization** - *Loo-Nin Teow and Kia-Fock Loe* |

| | | **Nonparametric Regularization of Decision Trees** - *Tobias Scheffer* |

| | | **Rough Sets and Ordinal Classification** - *Jan C. Bioch and Viara Popova* |

| | | **Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition** - *T. G. Dietterich* |

| | | **Improved bounds about on-line learning of smooth-functions of a single variable,** - *Philip M. Long* |

| | | **Applying formal concepts to learning systems validation** - *Volker Dötsch, Gunter Grieser and Steffen Lange* |

| | | **Learning Regular Languages Using Non Deterministic Finite Automata** - *François Denis, Aurélien Lemay and Alain Terlutte* |

| | | **Hypotheses Finding via Residue Hypotheses with the Resolution Principle** - *Akihiro Yamamoto and Bertram Fronhöfer* |

| | | **The Minimax Strategy for Gaussian Density Estimation** - *Eiji Takimoto and Manfred Warmuth* |

| | | **A Formalism for Relevance and Its Application in Feature Subset Selection** - *David A. Bell and Hui Wang* |

| | | **Pseudo-convergent Q-Learning by Competitive Pricebots** - *Jeffrey O. Kephart and Gerald J. Tesauro* |

| | | **Bias-Variance Error Bounds for Temporal Difference Updates** - *Michael Kearns and Satinder Singh* |

| | | **Bottom-Up Induction of Feature Terms** - *Eva Armengol and Enric Plaza* |

| | | **Learning to Probabilistically Identify Authoritative Documents** - *David Cohn and Huan Chang* |

| | | **Generalization Bounds for Decision Trees** - *Yishay Mansour and David McAllester* |

| | | **MadaBoost: A Modification of AdaBoost** - *Carlos Domingo and Osamu Watanabe* |

| | | **Multistrategy Discovery and Detection of Novice Programmer Errors** - *Raymund C. Sison, Masayuki Numao and Masamichi Shimura* |

| | | **MultiBoosting: A Technique for Combining Boosting and Wagging** - *Geoffrey I. Webb* |

| | | **Improved Generalization Through Explicit Optimization of Margins** - *Llew Mason, Peter L. Bartlett and Jonathan Baxter* |

| | | **An Average-Case Optimal One-Variable Pattern Language Learner** - *Rüdiger Reischuk and Thomas Zeugmann* |

| | | **Duality and Geometry in SVM Classifiers** - *Kristin P. Bennett and Erin J. Bredensteiner* |

| | | **Inferring Subclasses of Contextual Languages** - *J. D. Emerald, K. G. Subramanian and D. G. Thomas* |

| | | **An Adaptive Regularization Criterion for Supervised Learning** - *Dale Schuurmans and Finnegan Southey* |

| | | **Learning Chomsky-like Grammars for Biological Sequence Families** - *S. H. Muggleton, C. H. Bryant and A. Srinivasan* |

| | | **Learning languages and functions by erasing** - *Sanjay Jain, Efim Kinber, Steffen Lange, Rolf Wiehagen and Thomas Zeugmann* |

| | | **An Algorithm for Distributed Reinforcement Learning in Cooperative Multi-Agent Systems** - *Martin Lauer and Martin Riedmiller* |

| | | **Empirical Bayes for Learning to Learn** - *Tom Heskes* |

| | | **The Induction of Temporal Grammatical Rules from Multivariate Time Series** - *Gabriela Guimarães* |

| | | **Learning Context-Free Grammars with a Simplicity Bias** - *Pat Langley and Sean Stromsten* |

| | | **Adaptive Versus Nonadaptive Attribute-Efficient Learning** - *Peter Damaschke* |

| | | **Abstract Combinatorial Characterizations of Exact Learning via Queries** - *Jose Luis Balcázar, Jorge Castro and David Guijarro* |

| | | **Knowledge Discovery from Very Large Databases Using Frequent Concept Lattices** - *Kitsana Waiyamai and Lotfi Lakhal* |

| | | **Maximum Entropy Markov Models for Information Extraction and Segmentation** - *Andrew McCallum, Dayne Freitag and Fernando Pereira* |

| | | **Identification of Function Distinguishable Languages** - *Henning Fernau* |

| | | **Learning in Non-stationary Conditions: A Control Theoretic Approach** - *Jefferson Coelho and Rod Grupen* |

| | | **Phase Transitions in Relational Learning** - *Attilio Giordana and Lorenza Saitta* |

| | | **Probabilistic DFA Inference using Kullback-Leibler Divergence and Minimality** - *Franck Thollard, Pierre Dupont and Colin de la Higuera* |

| | | **Meta-Learning for Phonemic Annotation of Corpora** - *Véronique Hoste, Walter Daelemans, Erik Tjong Kim Sang and Steven Gillis* |

| | | **Bootstrap Methods for the Cost-Sensitive Evaluation of Classifiers** - *Dragos D. Margineantu and Thomas G. Dietterich* |

| | | **A Comparative Study of Cost-Sensitive Boosting Algorithms** - *Kai Ming Ting* |

| | | **Algorithm Selection using Reinforcement Learning** - *Michail G. Lagoudakis and Michael L. Littman* |

| | | **A Machine Learning Approach to Workflow Management** - *Joachim Herbst* |

| | | **Polynomial-time Learning of Elementary Formal Systems** - *Satoru Miyano, Ayumi Shinohara and Takeshi Shinohara* |

| | | **Using Learning by Discovery to Segment Remotely Sensed Images** - *Leen-Kiat Soh and Costas Tsatsoulis* |

| | | **Hardness Results for General Two-Layer Neural Networks** - *Christian Kuhlmann* |

| | | **Partial Linear Trees** - *Lu\'ıs Torgo* |

| | | **Classification with Multiple Latent Variable Models using Maximum Entropy Discrimination** - *Machiel Westerdijk and Wim Wiegerinck* |

| | | **Learning Probabilistic Models for Decision-Theoretic Navigation of Mobile Robots** - *Daniel Nikovski and Illah Nourbakhsh* |

| | | **Feature Subset Selection and Order Identification for Unsupervised Learning** - *Jennifer G. Dy and Carla E. Brodley* |

| | | **Maximizing Theory Accuracy Through Selective Reinterpretation** - *Shlomo Argamon-Engelson, Moshe Koppel and Hillel Walters* |

| | | **Learning to Fly: An Application of Hierarchical Reinforcement Learning** - *Malcolm Ryan and Mark Reid* |

| | | **FeatureBoost: A Meta-Learning Algorithm that Improves Model Robustness** - *Joseph O'Sullivan, John Langford, Rich Caruana and Avrim Blum* |

| | | **Randomizing Outputs to Increase Prediction Accuracy** - *Leo Breiman* |

| | | **Machine Learning for Subproblem Selection** - *Robert Moll, Theodore J. Perkins and Andrew G. Barto* |

| | | **Logical Analysis of Data with Decomposable Structures** - *Hirotaka Ono, Kazuhisa Makino and Toshihide Ibaraki* |

| | | **Data Reduction Techniques for Instance-Based Learning from Human/Computer Interface Data** - *Terran Lane and Carla E. Brodley* |

| | | **Learning from Positive and Unlabeled Examples** - *Fabien Letouzey, François Denis and Rémi Gilleron* |

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

| | | **Using a Symbolic Machine Learning Tool to Refine Lexico-syntactic Patterns** - *Emmanuel Morin and Emmanuelle Martienne* |

| | | **Special Issue of Machine Learning on Information Retrieval Introduction** - *Jaime Carbonell, Yiming Yang and William Cohen* |

| | | **Learning Filaments** - *Geoffrey J. Gordon and Andrew Moore* |

| | | **Conceptual Classifications Guided by a Concept Hierarchy** - *Yuhsuke Itoh and Makoto Haraguchi* |

| | | **The Effect of the Input Density Distribution on Kernel-based Classifiers** - *Christopher K. I. Williams and Matthias Seeger* |

| | | **On the Efficiency of Noise-Tolerant PAC Algorithms Derived from Statistical Queries** - *Jeffrey Jackson* |

| | | **Clustering the Users of Large Web Sites into Communities** - *Georgios Paliouras, Christos Papatheodorou, Vangelis Karkaletsis and Constantine D. Spyropoulos* |

| | | **A Study on the Performance of Large Bayes Classifier** - *Dimitris Meretakis, Hongjun Lu and Beat Wüthrich* |

| | | **Unlearning Helps** - *Ganesh Baliga, John Case, Wolfgang Merkle and Frank Stephan* |

| | | **A Study of Reinforcement Learning in the Continuous Case by the Means of Viscosity Solutions** - *Rémi Munos* |

| | | **A Probabilistic Identification Result** - *Eric McCreath* |

| | | **The Last-Step Minimax Algorithm** - *Eiji Takimoto and Manfred K. Warmuth* |

| | | **Sparse Greedy Matrix Approximation for Machine Learning** - *Alex J. Smola and Bernhard Schölkopf* |

| | | **Beyond Occam's Razor: Process-Oriented Evaluation** - *Pedro Domingos* |

| | | **Shaping in Reinforcement Learning by Changing the Physics of the Problem** - *Jette Randløv* |

| | | **A Bayesian Framework for Reinforcement Learning** - *Malcolm Strens* |

| | | **Image Color Constancy Using EM and Cached Statistics** - *Charles Rosenberg* |

| | | **Towards an Algorithmic Statistics** - *Peter Gács, John Tromp and Paul Vitányi* |

| | | **Hidden Markov Models with Patterns and Their Application to Integrated Circuit Testing** - *Laurent Bréhélin, Olivier Gascuel and Gilles Caraux* |

| | | **The Complexity of Densest Region Detection** - *Shai Ben-David, Nadav Eiron and Hans Ulrich Simon* |

| | | **Using Knowledge to Speed Learning: A Comparison Knowledge-based Cascade-correlation and Multi-task Learning** - *Thomas R. Shultz and Francois Rivest* |

| | | **A Divide and Conquer Approach to Learning from Prior Knowledge** - *Eric Chown and Thomas G. Dietterich* |

| | | **Support Vector Machine Active Learning with Applications to Text Classification** - *Simon Tong and Daphne Koller* |

| | | **Multi-Agent Q-learning and Regression Trees for Automated Pricing Decisions** - *Manu Sridharan and Gerald Tesauro* |

| | | **Reinforcement Learning in POMDP's via Direct Gradient Ascent** - *Jonathan Baxter and Peter L. Bartlett* |

| | | **Toward an Explanatory Similarity Measure for Nearest-Neighbor Classification** - *Mathieu Latourrette* |

| | | **X-means: Extending K-means with Efficient Estimation of the Number of Clusters** - *Dan Pelleg and Andrew Moore* |

| | | **Nonparametric Time Series Prediction Through Adaptive Model Selection** - *Ron Meir* |

| | | **A Normative Examination of Ensemble Learning Algorithms** - *David M. Pennock, Pedrito Maynard-Reid II, C. Lee Giles and Eric Horvitz* |

| | | **Combination of Estimation Algorithms and Grammatical Inference Techniques to Learn Stochastic Context-Free Grammars** - *Francisco Nevado, Joan-Andreu Sánchez and José -Miguel Bened\'ı* |

| | | **Lightweight Rule Induction** - *Sholom M. Weiss and Nitin Indurkhya* |

| | | **Convergence Problems of General-Sum Multiagent Reinforcement Learning** - *Michael Bowling* |

| | | **A Model of Inductive Bias Learning** - *J. Baxter* |

| | | **Robust Learning Aided by Context** - *John Case, Sanjay Jain, Matthias Ott, Arun Sharma and Frank Stephan* |

| | | **Partially Supervised Text Classification: Combining Labeled and Unlabeled Documents Using an EM-like Scheme** - *Carsten Lanquillon* |

| | | **Refining Numerical Constants in First Order Logic Theories** - *Marco Botta and Roberto Piola* |

| | | **Practical Reinforcement Learning in Continuous Spaces** - *William D. Smart and Leslie Pack Kaelbling* |

| | | **A Comparison of Ranking Methods for Classification Algorithm Selection** - *Pavel Brazdil and Carlos Soares* |

| | | **Learning from Approximate Data** - *Shirley Cheung* |

| | | **A New Framework for Discovering Knowledge from Two-Dimensional Structured Data Using Layout Formal Graph System** - *Tomoyuki Uchida, Yuko Itokawa, Takayoshi Shoudai, Tetsuhiro Miyahara and Yasuaki Nakamura* |

| | | **Boosting Using Branching Programs** - *Yishay Mansour and David McAllester* |

| | | **Barrier Boosting** - *G. Rätsch, M. Warmuth, S. Mika, T. Onoda, S. Lemm and K. R. Müller* |

| | | **Localized Boosting** - *Ron Meir, Ran El-Yaniv and Shai Ben-David* |

| | | **Hierarchical Unsupervised Learning** - *Shivakumar Vaithyanathan and Byron Dom* |

| | | **Generalized Average-Case Analyses of the Nearest Neighbor Algorithm** - *Seishi Okamoto and Nobuhiro Yugami* |

| | | **The Utilization of Context Signals in the Analysis of ABR Potentials by Application of Neural Networks** - *Andrzej Izworski, Ryszard Tadeusiewicz and Andrzej Paslawski* |

| | | **Online Ensemble Learning: An Empirical Study** - *Alan Fern and Robert Givan* |

| | | **Minimum description length induction, Bayesianism, and Kolmogorov complexity** - *P. M. Vitányi and M. Li* |

| | | **Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers** - *Erin L. Allwein, Robert E. Schapire and Yoram Singer* |

| | | **Learning Curved Multinomial Subfamilies for Natural Language Processing and Information Retrieval** - *Keith Hall and Thomas Hofmann* |

| | | **An Improved On-line Algorithm for Learning Linear Evaluation Functions** - *Peter Auer* |

| | | **An Empirical Study of MetaCost Using Boosting Algorithms** - *Kai Ming Ting* |

| | | **Clustered Partial Linear Regression** - *Luíz Torgo and Joaquim Pinto da Costa* |

| | | **Instance Pruning as an Information Preserving Problem** - *Marc Sebban and Richard Nock* |

| September | | **On-Line Learning with Linear Loss Constraints** - *David P. Helmbold, Nicholas Littlestone and Philip M. Long* |

| | | **Apple Tasting** - *David P. Helmbold, Nicholas Littlestone and Philip M. Long* |

| December | | **Testing Problems with Sublearning Sample Complexity** - *Michael Kearns and Dana Ron* |

| | | **Inductive Synthesis of Recursive Processes from Logical Properties** - *Shigetomo Kimura, Atsushi Togashi and Norio Shiratori* |

| | | **Algorithmic Learning Theory, 11th International Conference, ALT 2000, Sydney, Australia, December 2000, Proceedings** - *Hiroki Arimura and Sanjay Jain and Arun Sharma* |

| | | **The Lob-Pass Problem** - *Jun-ichi Takeuchi, Naoki Abe and Shun-ichi Amari* |