ECML-PKDD 2006

82 papers

(Agnostic) PAC Learning Concepts in Higher-Order Logic Kee Siong Ng

A Discriminative Approach for the Retrieval of Images from Text Queries David Grangier, Florent Monay, Samy Bengio

A Kernel-Based Approach to Estimating Phase Shifts Between Irregularly Sampled Time Series: An Application to Gravitational Lenses Juan Carlos Cuevas-Tello, Peter Tiño, Somak Raychaudhury

A Selective Sampling Strategy for Label Ranking Massih-Reza Amini, Nicolas Usunier, François Laviolette, Alexandre Lacasse, Patrick Gallinari

Active Learning with Irrelevant Examples Dominic Mazzoni, Kiri Wagstaff, Michael C. Burl

An Adaptive Kernel Method for Semi-Supervised Clustering Bojun Yan, Carlotta Domeniconi

An Efficient Approximation to Lookahead in Relational Learners Jan Struyf, Jesse Davis, C. David Page Jr.

An Information-Theoretic Framework for High-Order Co-Clustering of Heterogeneous Objects Antonio D. Chiaravalloti, Gianluigi Greco, Antonella Guzzo, Luigi Pontieri

Approximate Policy Iteration for Closed-Loop Learning of Visual Tasks Sébastien Jodogne, Cyril Briquet, Justus H. Piater

Automatically Evolving Rule Induction Algorithms Gisele L. Pappa, Alex Alves Freitas

B-Matching for Spectral Clustering Tony Jebara, Vlad Shchogolev

Bagging Using Statistical Queries Anneleen Van Assche, Hendrik Blockeel

Bandit Based Monte-Carlo Planning Levente Kocsis, Csaba Szepesvári

Batch Classification with Applications in Computer Aided Diagnosis Volkan Vural, Glenn Fung, Balaji Krishnapuram, Jennifer G. Dy, R. Bharat Rao

Bayesian Active Learning for Sensitivity Analysis Tobias Pfingsten

Bayesian Learning of Markov Network Structure Aleks Jakulin, Irina Rish

Bayesian Learning with Mixtures of Trees Jussi Kollin, Mikko Koivisto

Boosting in PN Spaces Martin Scholz

Cascade Evaluation of Clustering Algorithms Laurent Candillier, Isabelle Tellier, Fabien Torre, Olivier Bousquet

Case-Based Label Ranking Klaus Brinker, Eyke Hüllermeier

Classification with Support Hyperplanes Georgi I. Nalbantov, Jan C. Bioch, Patrick J. F. Groenen

Combinatorial Markov Random Fields Ron Bekkerman, Mehran Sahami, Erik G. Learned-Miller

Constant Rate Approximate Maximum Margin Algorithms Petroula Tsampouka, John Shawe-Taylor

Cost-Sensitive Decision Tree Learning for Forensic Classification Jason V. Davis, Jungwoo Ha, Christopher J. Rossbach, Hany E. Ramadan, Emmett Witchel

Cost-Sensitive Learning of SVM for Ranking Jun Xu, Yunbo Cao, Hang Li, Yalou Huang

Deconvolutive Clustering of Markov States Ata Kabán, Xin Wang

Distributional Features for Text Categorization Xiao-Bing Xue, Zhi-Hua Zhou

Diversified SVM Ensembles for Large Data Sets Ivor W. Tsang, András Kocsor, James T. Kwok

Dynamic Integration with Random Forests Alexey Tsymbal, Mykola Pechenizkiy, Padraig Cunningham

Efficient Convolution Kernels for Dependency and Constituent Syntactic Trees Alessandro Moschitti

Efficient Inference in Large Conditional Random Fields Trevor Cohn

Efficient Large Scale Linear Programming Support Vector Machines Suvrit Sra

Efficient Non-Linear Control Through Neuroevolution Faustino J. Gomez, Jürgen Schmidhuber, Risto Miikkulainen

Efficient Prediction-Based Validation for Document Clustering Derek Greene, Padraig Cunningham

EM Algorithm for Symmetric Causal Independence Models Rasa Jurgelenaite, Tom Heskes

Ensembles of Nearest Neighbor Forecasts Dragomir Yankov, Dennis DeCoste, Eamonn J. Keogh

Evaluating Feature Selection for SVMs in High Dimensions Roland Nilsson, José M. Peña, Johan Björkegren, Jesper Tegnér

Evaluating Misclassifications in Imbalanced Data William Elazmeh, Nathalie Japkowicz, Stan Matwin

Exploiting Extremely Rare Features in Text Categorization Péter Schönhofen, András A. Benczúr

Fast Spectral Clustering of Data Using Sequential Matrix Compression Bo Chen, Bin Gao, Tie-Yan Liu, Yu-Fu Chen, Wei-Ying Ma

Fast Variational Inference for Gaussian Process Models Through KL-Correction Nathaniel John King, Neil D. Lawrence

Fisher Kernels for Relational Data Uwe Dick, Kristian Kersting

Graph Based Semi-Supervised Learning with Sharper Edges Hyunjung Shin, N. Jeremy Hill, Gunnar Rätsch

Guiding the Search in the NO Region of the Phase Transition Problem with a Partial Subsumption Test Samuel Wieczorek, Gilles Bisson, Mirta B. Gordon

Improvement of Systems Management Policies Using Hybrid Reinforcement Learning Gerald Tesauro, Nicholas K. Jong, Rajarshi Das, Mohamed N. Bennani

Improving Bayesian Network Structure Search with Random Variable Aggregation Hierarchies John Burge, Terran Lane

Improving Control-Knowledge Acquisition for Planning by Active Learning Raquel Fuentetaja, Daniel Borrajo

Improving the Ranking Performance of Decision Trees Bin Wang, Harry Zhang

Languages as Hyperplanes: Grammatical Inference with String Kernels Alexander Clark, Christophe Costa Florêncio, Chris Watkins

Learning in One-Shot Strategic Form Games Alon Altman, Avivit Bercovici-Boden, Moshe Tennenholtz

Learning Process Models with Missing Data Will Bridewell, Pat Langley, Steve Racunas, Stuart R. Borrett

Learning Stochastic Tree Edit Distance Marc Bernard, Amaury Habrard, Marc Sebban

Localized Alternative Cluster Ensembles for Collaborative Structuring Michael Wurst, Katharina Morik, Ingo Mierswa

Making Good Probability Estimates for Regression Michael Carney, Padraig Cunningham

Margin-Based Active Learning for Structured Output Spaces Dan Roth, Kevin Small

Missing Data in Kernel PCA Guido Sanguinetti, Neil D. Lawrence

Mixtures of Kikuchi Approximations Roberto Santana, Pedro Larrañaga, José Antonio Lozano

Multi-Class Ensemble-Based Active Learning Christine Körner, Stefan Wrobel

Multiple-Instance Learning via Random Walk Dong Wang, Jianmin Li, Bo Zhang

On Testing the Missing at Random Assumption Manfred Jaeger

PAC-Learning of Markov Models with Hidden State Ricard Gavaldà, Philipp W. Keller, Joelle Pineau, Doina Precup

Patching Approximate Solutions in Reinforcement Learning Min Sub Kim, William T. B. Uther

Pertinent Background Knowledge for Learning Protein Grammars Christopher H. Bryant, Daniel Fredouille, Alex Wilson, Channa K. Jayawickreme, Steven Jupe, Simon Topp

Prioritizing Point-Based POMDP Solvers Guy Shani, Ronen I. Brafman, Solomon Eyal Shimony

Reinforcement Learning for MDPs with Constraints Peter Geibel

Revisiting Fisher Kernels for Document Similarities Martin Nyffenegger, Jean-Cédric Chappelier, Éric Gaussier

Right of Inference: Nearest Rectangle Learning Revisited Byron J. Gao, Martin Ester

Robust Probabilistic Calibration Stefan Rüping

Scaling Model-Based Average-Reward Reinforcement Learning for Product Delivery Scott Proper, Prasad Tadepalli

Sequence Discrimination Using Phase-Type Distributions Jérôme Callut, Pierre Dupont

Skill Acquisition via Transfer Learning and Advice Taking Lisa Torrey, Jude W. Shavlik, Trevor Walker, Richard Maclin

Spline Embedding for Nonlinear Dimensionality Reduction Shiming Xiang, Feiping Nie, Changshui Zhang, Chunxia Zhang

Subspace Metric Ensembles for Semi-Supervised Clustering of High Dimensional Data Bojun Yan, Carlotta Domeniconi

Task-Driven Discretization of the Joint Space of Visual Percepts and Continuous Actions Sébastien Jodogne, Justus H. Piater

The Minimum Volume Covering Ellipsoid Estimation in Kernel-Defined Feature Spaces Alexander N. Dolia, Tijl De Bie, Christopher J. Harris, John Shawe-Taylor, D. M. Titterington

TildeCRF: Conditional Random Fields for Logical Sequences Bernd Gutmann, Kristian Kersting

To Select or to Weigh: A Comparative Study of Model Selection and Model Weighing for SPODE Ensembles Ying Yang, Geoffrey I. Webb, Jesús Cerquides, Kevin B. Korb, Janice R. Boughton, Kai Ming Ting

Toward Robust Real-World Inference: A New Perspective on Explanation-Based Learning Gerald DeJong

Transductive Gaussian Process Regression with Automatic Model Selection Quoc V. Le, Alexander J. Smola, Thomas Gärtner, Yasemin Altun

Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data Corneliu Henegar, Karine Clément, Jean-Daniel Zucker

Variational Bayesian Dirichlet-Multinomial Allocation for Exponential Family Mixtures Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Kriegel

Why Is Rule Learning Optimistic and How to Correct It Martin Mozina, Janez Demsar, Jure Zabkar, Ivan Bratko