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The
Twentieth International Conference August 21-24,
2003 |
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The
Twentieth International Conference August 21-24,
2003 |
Learning
Distance Functions using Equivalence Relations
[Abstract] [Full paper]
Aharon Bar Hillel - Hebrew University of Jerusalem
Tomer Hertz - Hebrew University of Jerusalem
Noam Shental - Hebrew University of Jerusalem
Daphna Weinshall - Hebrew University of Jerusalem
Online
Choice of Active Learning Algorithms
[Abstract] [Full paper]
Yoram Baram - Technion - Israel Institute of Technology
Ran El-Yaniv - Technion - Israel Institute of Technology
Kobi Luz - Technion - Israel Institute of Technology
Learning
Logic Programs for Layout Analysis Correction
[Abstract] [Full paper]
Margherita Berardi - University of Bari
Michelangelo Ceci - University of Bari
Floriana Esposito - University of Bari
Donato Malerba - University of Bari
Multi-Objective
Programming in SVMs
[Abstract] [Full paper]
Jinbo Bi - Rensselaer Polytechnic Institute
Regression
Error Characteristic Curves
[Abstract] [Full paper]
Jinbo Bi - Rensselaer Polytechnic Institute
Kristin Bennett - Rensselaer Polytechnic Institute
Choosing
between two learning algorithms based on calibrated tests
[Abstract] [Full paper]
Remco Bouckaert - University of Waikato
Incorporating
Diversity in Active Learning with Support Vector Machines
[Abstract] [Full paper]
Klaus Brinker - University of Paderborn
The
Use of the Ambiguity Decomposition in Neural Network Ensemble Learning
Methods
[Abstract] [Full paper]
Gavin Brown - University of Birmingham
Jeremy Wyatt - University of Birmingham
Tractable
Bayesian Learning of Tree Augmented Naive Bayes Models
[Abstract] [Full paper]
Jesús Cerquides - Universitat de Barcelona
Ramon López de Màntaras - Consejo Superior de Investigaciones
Cientificas
AWESOME:
A General Multiagent Learning Algorithm that Converges in Self-Play and
Learns a Best Response Against Stationary Opponents
[Abstract] [Full paper]
Vincent Conitzer - Carnegie Mellon University
Tuomas Sandholm - Carnegie Mellon University
BL-WoLF:
A Framework For Loss-Bounded Learnability In Zero-Sum Games
[Abstract] [Full paper]
Vincent Conitzer - Carnegie Mellon University
Tuomas Sandholm - Carnegie Mellon University
Semi-Supervised
Learning of Mixture Models
[Abstract] [Full paper]
Fabio Cozman - University of Sao Paulo
Ira Cohen - University of Illinois at Urbana-Champaign
Marcelo Cirelo - University of Sao Paulo
On
Kernel Methods for Relational Learning
[Abstract] [Full paper]
Chad Cumby - University of Illinois at Urbana-Champaign
Dan Roth - University of Illinois at Urbana-Champaign
Fast
Query-Optimized Kernel Machine Classification Via Incremental Approximate
Nearest Support Vectors
[Abstract] [Full paper]
Dennis DeCoste - Jet Propulsion Laboratory / Caltech
Dominic Mazzoni - Jet Propulsion Laboratory / Caltech
Relational
Instance Based Regression for Relational Reinforcement Learning
[Abstract] [Full paper]
Kurt Driessens - Catholic University of Leuven
Jan Ramon - Catholic University of Leuven
Design
for an Optimal Probe
[Abstract] [Full paper]
Michael Duff - Univeristy College London
Diffusion
Approximation for Bayesian Markov Chains
[Abstract] [Full paper]
Michael Duff - Univeristy College London
Using
the Triangle Inequality to Accelerate k-Means
[Abstract] [Full paper]
Charles Elkan - University of California, San Diego
Bayes
Meets Bellman: The Gaussian Process Approach to Temporal Difference Learning
[Abstract] [Full paper]
Yaakov Engel - Hebrew University
Shie Mannor - Massachusetts Institute of Technology
Ron Meir - Technion Institute of Technology
Action
Elimination and Stopping Conditions for Reinforcement Learning
[Abstract] [Full paper]
Eyal Even-Dar - Tel-Aviv University
Shie Mannor - MIT
Yishay Mansour - Tel-Aviv University
Utilizing
Domain Knowledge in Neuroevolution
[Abstract] [Full paper]
James Fan - University of Texas at Austin
Raymond Lau - University of Texas at Austin
Risto Miikkulainen - University of Texas at Austin
Boosting
Lazy Decision Trees
[Abstract] [Full paper]
Xiaoli Fern - Purdue University
Carla Brodley - Purdue University
Random
Projection for High Dimensional Data Clustering: A Cluster Ensemble Approach
[Abstract] [Full paper]
Xiaoli Fern - Purdue University
Carla Brodley - Purdue University
The
Geometry of ROC Space: Understanding Machine Learning Metrics through ROC
Isometrics
[Abstract] [Full paper]
Peter Flach - University of Bristol
An
Analysis of Rule Evaluation Metrics
[Abstract] [Full paper]
Johannes Fürnkranz - Austrian Research Institute for Artificial
Intelligence
Peter Flach - University of Bristol
Margin
Distribution and Learning
[Abstract] [Full paper]
Ashutosh Garg - IBM Almaden Research Center
Dan Roth - University of Illinois at Urbana-Champaign
Perceptron
Based Learning with Example Dependent and Noisy Costs
[Abstract] [Full paper]
Peter Geibel - TU Berlin
Fritz Wysotzki - TU Berlin
Hierarchical
Policy Gradient Algorithms
[Abstract] [Full paper]
Mohammad Ghavamzadeh - University of Massachusetts Amherst
Sridhar Mahadevan - University of Massachusetts Amherst
Solving
Noisy Linear Operator Equations by Gaussian Processes: Application to Ordinary
and Partial Differential Equations
[Abstract] [Full paper]
Thore Graepel - Microsoft Research
Correlated
Q-Learning
[Abstract] [Full paper]
Amy Greenwald - Brown University
Keith Hall - Brown University
Online
Ranking/Collaborative filtering using the Perceptron Algorithm
[Abstract] [Full paper]
Edward Harrington - The Australian National University
Goal-directed
Learning to Fly
[Abstract] [Full paper]
Andrew Isaac - University of New South Wales
Claude Sammut - University of New South Wales
Probabilistic
Classifiers and the Concepts they Recognize
[Abstract] [Full paper]
Manfred Jaeger - MPI Informatik
Avoiding
Bias when Aggregating Relational Data with Degree Disparity
[Abstract] [Full paper]
David Jensen - University of Massachusetts Amherst
Jennifer Neville - University of Massachusetts Amherst
Michael Hay - University of Massachusetts Amherst
A
New Boosting Algorithm Using Input-Dependent Regularizer
[Abstract] [Full paper]
Rong Jin - Carnegie Mellon Univeristy
Yan Liu - Carnegie Mellon Univeristy
Luo Si - Carnegie Mellon Univeristy
Jaime Carbonell - Carnegie Mellon Univeristy
Alex Hauptmann - Carnegie Mellon Univeristy
A
Faster Iterative Scaling Algorithm For Conditional Exponential Model
[Abstract] [Full paper]
Rong Jin - Carnegie Mellon University
Rong Yan - Carnegie Mellon University
Jian Zhang - Carnegie Mellon University
Alex Hauptmann - Carnegie Mellon University
Transductive
Learning via Spectral Graph Partitioning
[Abstract] [Full paper]
Thorsten Joachims - Cornell University
Evolving
Strategies for Focused Web Crawling
[Abstract] [Full paper]
Judy Johnson - NEC Laboratories America, Pennsylvania State University
Kostas Tsioutsiouliklis - NEC Laboratories America
C. Lee Giles - Pennsylvania State University, NEC Laboratories America
Exploration
in Metric State Spaces
[Abstract] [Full paper]
Sham Kakade - University College London
Michael Kearns - University of Pennsylvania
John Langford - IBM TJ Watson Research Center
The
Significance of Temporal-Difference Learning in Self-Play Training TD-Rummy
versus EVO-rummy
[Abstract] [Full paper]
Jugal Kalita - University of Colorado at Colorado Springs
Cliff Kotnik - University of Colorado at Colorado Springs
Representational
Issues in Meta-Learning
[Abstract] [Full paper]
Alexandros Kalousis - University of Geneva
Melanie Hilario - University of Geneva
Marginalized
Kernels Between Labeled Graphs
[Abstract] [Full paper]
Hisashi Kashima - IBM Tokyo Research Laboratory
Koji Tsuda - Max Plank Institute for Biological Cybernetics / AIST
Computational Biology Center
Akihiro Inokuchi - IBM Tokyo Research Laboratory
Informative
Discriminant Analysis
[Abstract] [Full paper]
Samuel Kaski - Helsinki University of Technology
Jaakko Peltonen - Helsinki University of Technology
Characteristics
of Long-term Learning in Soar and its Application to the Utility Problem
[Abstract] [Full paper]
William Kennedy - George Mason University
Kenneth De Jong - George Mason University
Unsupervised
Learning with Permuted Data
[Abstract] [Full paper]
Sergey Kirshner - University of California, Irvine
Sridevi Parise - University of California, Irvine
Padhraic Smyth - University of California, Irvine
Discriminative
Gaussian Mixture Models: A Comparison with Kernel Classifiers
[Abstract] [Full paper]
Aldebaro Klautau - UCSD
Nikola Jevtic - UCSD
Alon Orlitsky - UCSD
A
Kernel Between Sets of Vectors
[Abstract] [Full paper]
Risi Kondor - Columbia University
Tony Jebara - Columbia University
Visual
Learning by Evolutionary Feature Synthesis
[Abstract] [Full paper]
Krzysztof Krawiec - University of California, Riverside
Bir Bhanu - University of California, Riverside
Classification
of Text Documents Based on Minimum System Entropy
[Abstract] [Full paper]
Raghu Krishnapuram - IBM India Research Lab
Krishna Chitrapura - IBM India Research Lab
Sachindra Joshi - IBM India Research Lab
Finding
Underlying Connections: A Fast Graph-Based Method for Link Analysis and
Collaboration Queries
[Abstract] [Full paper]
Jeremy Kubica - Carnegie Mellon University
Andrew Moore - Carnegie Mellon University
David Cohn - Carnegie Mellon University
Jeff Schneider - Carnegie Mellon University
Learning
with Idealized Kernels
[Abstract] [Full paper]
James Kwok - Hong Kong University of Science and Technology
Ivor Tsang - Hong Kong University of Science and Technology
The
Pre-Image Problem in Kernel Methods
[Abstract] [Full paper]
James Kwok - Hong Kong University of Science and Technology
Ivor Tsang - Hong Kong University of Science and Technology
Improving
accuracy and cost of two-class and multi-class probabilistic classifiers
using ROC curves
[Abstract] [Full paper]
Nicolas Lachiche - LSIIT
Peter Flach - University of Bristol
Reinforcement
Learning as Classification: Leveraging Modern Classifiers
[Abstract] [Full paper]
Michail Lagoudakis - Duke University
Ronald Parr - Duke University
Robust
Induction of Process Models from Time-Series Data
[Abstract] [Full paper]
Pat Langley - Stanford University/ISLE
Dileep George - Stanford University
Stephen Bay - Stanford University/ISLE
Kazumi Saito - NTT Communication Science Laboratories
The
Influence of Reward on the Speed of Reinforcement Learning: An Analysis
of Shaping
[Abstract] [Full paper]
Adam Laud - University of Illinois at Urbana-Champaign
Gerald DeJong - University of Illinois at Urbana-Champaign
Learning
with Positive and Unlabeled Examples Using Weighted Logistic Regression
[Abstract] [Full paper]
Wee Sun Lee - National University of Singapore
Bing Liu - University of Illinois, Chicago
Linear
Programming Boosting for Uneven Datasets
[Abstract] [Full paper]
Jurij Leskovec - Jozef Stefan Institute
John Shawe-Taylor - Royal Holloway University of London
Text
Classification Using Stochastic Keyword Generation
[Abstract] [Full paper]
Cong Li - Microsoft Research Asia
Ji-Rong Wen - Microsoft Research Asia
Hang Li - Microsoft Research Asia
A
Loss Function Analysis for Classification Methods in Text Categorization
[Abstract] [Full paper]
Fan Li - Carnegie Mellon University
Yiming Yang - Carnegie Mellon University
Decision
Tree with Better Ranking
[Abstract] [Full paper]
Charles Ling - University of Western Ontario
Robert (Jun) Yan - University of Western Ontario
An
Evaluation on Feature Selection for Text Clustering
[Abstract] [Full paper]
Tao Liu - Nankai University, Tianjin
Shengping Liu - Peking University, Beijing
Zheng Chen - Microsoft Research Asia
Wei-Ying Ma - Microsoft Research Asia
Link-based
Classification
[Abstract] [Full paper]
Qing Lu - University of Maryland
Lise Getoor - University of Maryland
Hierarchical
Latent Knowledge Analysis for Co-occurrence Data
[Abstract] [Full paper]
Hiroshi Mamitsuka - Kyoto University
The
Cross Entropy method for Fast Policy Search
[Abstract] [Full paper]
Shie Mannor - Massachusetts Institute of Technology
Reuven Rubinstein - Technion
Yohai Gat - Technion
The
Set Covering Machine with Data-Dependent Half-Spaces
[Abstract] [Full paper]
Mario Marchand - University of Ottawa
Mohak Shah - University of Ottawa
John Shawe-Taylor - Royal Holloway, University of London
Marina Sokolova - University of Ottawa
Identifying
Predictive Structures in Relational Data Using Multiple Instance Learning
[Abstract] [Full paper]
Amy McGovern - University of Massachusetts Amherst
David Jensen - University of Massachusetts Amherst
Planning
in the Presence of Cost Functions Controlled by an Adversary
[Abstract] [Full paper]
H. Brendan McMahan - Carnegie Mellon University
Avrim Blum - Carnegie Mellon University
Geoffrey Gordon - Carnegie Mellon University
Using
Linear-threshold Algorithms to Combine Multi-class Sub-experts
[Abstract] [Full paper]
Chris Mesterharm - Rutgers University
Optimal
Reinsertion: A new search operator for accelerated and more accurate Bayesian
network structure learning
[Abstract] [Full paper]
Andrew Moore - Carnegie Mellon University
Weng-Keen Wong - Carnegie Mellon University
Error
Bounds for Approximate Policy Iteration
[Abstract] [Full paper]
Remi Munos - Ecole Polytechnique
Machine
Learning with Hyperkernels
[Abstract] [Full paper]
Cheng Soon Ong - Australian National University
Alex Smola - Australian National University
Justification-based
Multiagent Learning
[Abstract] [Full paper]
Santi Ontañón - IIIA-CSIC
Enric Plaza - IIIA-CSIC
Mixtures
of Conditional Maximum Entropy Models
[Abstract] [Full paper]
Dmitry Pavlov - Yahoo! Inc.
Alexandrin Popescul - University of Pennsylvania
David Pennock - Overture Services, Inc.
Lyle Ungar - University of Pennsylvania
Online
Feature Selection using Grafting
[Abstract] [Full paper]
Simon Perkins - Los Alamos National Laboratory
James Theiler - Los Alamos National Laboratory
Weighted
Order Statistic Classifiers with Large Rank-Order Margin
[Abstract] [Full paper]
Reid Porter - Los Alamos National Lab
Damian Eads - Los Alamos National Lab
Don Hush - Los Alamos National Lab
James Theiler - Los Alamos National Lab
Relativized
Options: Choosing the Right Transformation
[Abstract] [Full paper]
Balaraman Ravindran - University of Massachusetts, Amherst
Andrew Barto - University of Massachusetts, Amherst
Tackling
the Poor Assumptions of Naive Bayes Text Classifiers
[Abstract] [Full paper]
Jason Rennie - Massachusets Institute of Technology
Lawrence Shih - Massachusets Institute of Technology
Jaime Teevan - Massachusets Institute of Technology
David R. Karger - Massachusets Institute of Technology
Learning
with Knowledge from Multiple Experts
[Abstract] [Full paper]
Matthew Richardson - University of Washington
Pedro Domingos - University of Washington
Combining
TD-learning with Cascade-correlation Networks
[Abstract] [Full paper]
Francois Rivest - Université de Montréal
Doina Precup - McGill University
Kernel
PLS-SVC for Linear and Nonlinear Classification
[Abstract] [Full paper]
Roman Rosipal - NASA Ames Research Center
Leonard Trejo - NASA Ames Research Center
Bryan Matthews - NASA Ames Research Center
Stochastic
Local Search in k-term DNF Learning
[Abstract] [Full paper]
Ulrich Rueckert - Albert-Ludwigs-Universität Freiburg
Stefan Kramer - Technische Universität München
Q-Decomposition
for Reinforcement Learning Agents
[Abstract] [Full paper]
Stuart Russell - University of California, Berkeley
Andrew Zimdars - University of California, Berkeley
Adaptive
Overrelaxed Bound Optimization Methods
[Abstract] [Full paper]
Ruslan Salakhutdinov - University of Toronto
Sam Roweis - University of Toronto
Optimization
with EM and Expectation-Conjugate-Gradient
[Abstract] [Full paper]
Ruslan Salakhutdinov - University of Toronto
Sam Roweis - University of Toronto
Zoubin Ghahramani - University College London
TD(0)
Converges Provably Faster than the Residual Gradient Algorithm
[Abstract] [Full paper]
Ralf Schoknecht - University of Karlsruhe
Artur Merke - University of Dortmund
On
State Merging in Grammatical Inference: A Statistical Approach for Dealing
with Noisy Data
[Abstract] [Full paper]
Marc Sebban - EURISE
Jean-Christophe Janodet - EURISE
Text
Bundling: Statistics Based Data-Reduction
[Abstract] [Full paper]
Lawrence Shih - Massachusetts Institute of Technology
Jason Rennie - Massachusetts Institute of Technology
Yu-Han Chang - Massachusetts Institute of Technology
David R. Karger - Massachusetts Institute of Technology
Flexible
Mixture Model for Collaborative Filtering
[Abstract] [Full paper]
Luo Si - Carnegie Mellon University
Rong Jin - Carnegie Mellon University
Learning
Predictive State Representations
[Abstract] [Full paper]
Satinder Singh - University of Michigan
Michael Littman - Rutgers University
Nicholas Jong - The University of Texas at Austin
David Pardoe - The University of Texas at Austin
Peter Stone - The University of Texas at Austin
Weighted
Low-Rank Approximations
[Abstract] [Full paper]
Nathan Srebro - MIT
Tommi Jaakkola - MIT
Learning
To Cooperate in a Social Dilemma: A Satisficing Approach to Bargaining
[Abstract] [Full paper]
Jeffrey Stimpson - Brigham Young University
Michael Goodrich - Brigham Young University
Evolutionary
MCMC sampling and optimization in discrete spaces
[Abstract] [Full paper]
Malcolm Strens - QinetiQ Ltd
Learning
on the Test Data: Leveraging Unseen Features
[Abstract] [Full paper]
Ben Taskar - Stanford University
Ming Fai Wong - Stanford University
Daphne Koller - Stanford University
Low
Bias Bagged Support Vector Machines
[Abstract] [Full paper]
Giorgio Valentini - Universita' di Genova
Thomas Dietterich - Oregon State University, Corvallis
SimpleSVM
[Abstract] [Full paper]
S V N Vishwanathan - NICTA
Alex Smola - ANU
Narashima Murty - Indian Institute of Science
Testing
Exchangeability On-Line
[Abstract] [Full paper]
Vladimir Vovk - Royal Holloway, University of London
Ilia Nouretdinov - Royal Holloway, University of London
Alex Gammerman - Royal Holloway, University of London
Model-based
Policy Gradient Reinforcement Learning
[Abstract] [Full paper]
Xin Wang - Oregon State University
Thomas Dietterich - Oregon State University
Learning
Mixture Models with the Latent Maximum Entropy Principle
[Abstract] [Full paper]
Shaojun Wang - Unversity of Toronto
Dale Schuurmans - University of Waterloo
Fuchun Peng - University of Waterloo
Yunxin Zhao - University of Missouri at Columbia
Principled
Methods for Advising Reinforcement Learning Agents
[Abstract] [Full paper]
Eric Wiewiora - University of California, San Diego
Garrison Cottrell - University of California, San Diego
Charles Elkan - University of California, San Diego
DISTILL:
Learning Domain-Specific Planners by Example
[Abstract] [Full paper]
Elly Winner - Carnegie Mellon University
Manuela Veloso - Carnegie Mellon University
Bayesian
Network Anomaly Pattern Detection for Disease Outbreaks
[Abstract] [Full paper]
Weng-Keen Wong - Carnegie Mellon University
Andrew Moore - Carnegie Mellon University
Gregory Cooper - University of Pittsburgh
Michael Wagner - University of Pittsburgh
Adaptive
Feature-Space Conformal Transformation for Imbalanced-Data Learning
[Abstract] [Full paper]
Gang Wu - University of California, Santa Barbara
Edward Chang - University of California, Santa Barbara
New
\\nu-Support Vector Machines and their sequential minimal optimization
[Abstract] [Full paper]
Xiaoyun Wu - University at Buffalo
Rohini Srihari - University at Buffalo
Cross-Entropy
Directed Embedding of Network Data
[Abstract] [Full paper]
Takeshi Yamada - NTT Communication Science Laboratories
Kazumi Saito - NTT Communication Science Laboratories
Naonori Ueda - NTT Communication Science Laboratories
Decision-tree
Induction from Time-series Data Based on a Standard-example Split Test
[Abstract] [Full paper]
Yuu Yamada - Yokohama National University
Einoshin Suzuki - Yokohama National University
Hideto Yokoi - Chiba University Hospital
Katsuhiko Takabayashi - Chiba University Hospital
Optimizing
Classifier Performance via an Approximation to the Wilcoxon-Mann-Whitney
Statistic
[Abstract] [Full paper]
Lian Yan - CSG Systems, Inc.
Robert Dodier - CSG Systems, Inc.
Michael Mozer - University of Colorado at Boulder
Richard Wolniewicz - CSG Systems, Inc.
Feature
Selection for High-Dimensional Data: A Fast Correlation-Based Filter Solution
[Abstract] [Full paper]
Lei Yu - Arizona State University
Huan Liu - Arizona State University
Isometric
Embedding and Continuum ISOMAP
[Abstract] [Full paper]
Hongyuan Zha - Penn State University
Zhenyue Zhang - Zhejiang University
Learning
Metrics via Discriminant Kernels and Multidimensional Scaling: Toward Expected
Euclidean Representation
[Abstract] [Full paper]
Zhihua Zhang - The Hong Kong University of Science and Technology
Learning
from Attribute Value Taxonomies and Partially Specified Instances
[Abstract] [Full paper]
Jun Zhang - Iowa State University
Vasant Honavar - Iowa State University
Modified
Logistic Regression: An Approximation to SVM and Its Applications in Large-Scale
Text Categorization
[Abstract] [Full paper]
Jian Zhang - Carnegie Mellon University
Rong Jin - Carnegie Mellon University
Yiming Yang - Carnegie Mellon University
Alex Hauptmann - Carnegie Mellon University
Exploration
and Exploitation in Adaptive Filtering Based on Bayesian Active Learning
[Abstract] [Full paper]
Yi Zhang - Carnegie Mellon University
Wei Xu - NEC Laboratories America
Jamie Callan - Carnegie Mellon University
On
the Convergence of Boosting Procedures
[Abstract] [Full paper]
Tong Zhang - IBM T.J. Watson Research Center
Bin Yu - University of California at Berkeley
Semi-Supervised
Learning Using Gaussian Fields and Harmonic Functions
[Abstract] [Full paper]
Xiaojin Zhu - Carnegie Mellon University
Zoubin Ghahramani - University College London
John Lafferty - Carnegie Mellon University
Eliminating
Class Noise in Large Datasets
[Abstract] [Full paper]
Xingquan Zhu - University of Vermont
Xindong Wu - University of Vermont
Qijun Chen - University of Vermont
Online
Convex Programming and Generalized Infinitesimal Gradient Ascent
[Abstract] [Full paper]
Martin Zinkevich - Carnegie Mellon University
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