ECML Full Papers | ECML Short Papers | PKDD Full Papers | PKDD Short Papers

ECML Full Papers


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

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

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

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

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

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

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

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

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

Fisher Kernels for Relational Data
Uwe Dick, Kristian Kersting

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

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

Learning Markov Models with Hidten State
Ricard Gavalda, Philipp Keller, Joelle Pineau, Doina Precup

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

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

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

Bayesian Learning of Markov Network Structure
Aleks Jakulin, Irina Rish

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

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

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

Deconvolutive Clustering of Markov States
Ata Kaban, Xin Wang

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

Fast Variational Inference for Gaussian Process Models through KL-Correction
Nathaniel King, Neil Lawrence

Bandit Based Monte-Carlo Planning
Levente Kocsis, Csaba Szepesvári

Bayesian Learning with Mixtures of Trees
Jussi Kollin, Mikko Koivisto

Transductive Gaussian Process Regression with Automatic Model Selection
Quoc V. Le, Australia

Alex Smola, Australia
Thomas Gärtner, Yasemin Altun

Efficient Convolution Kernels for Dependency and Constituent Syntactic Trees
Alessandro Moschitti

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

Automatically Evolving Rule Induction Algorithms
Gisele Pappa, Alex Freitas

Bayesian Active Learning for Sensitivity Analysis
Tobias Pfingsten

Mixtures of Kikuchi Approximations
Roberto Santana, Pedro Larrańaga, Jose A. Lozano

Boosting in PN Spaces
Martin Scholz

Prioritized Value Iteration for POMDPs
Guy Shani, Ronen Brafman, Solomon Shimony

Graph Based Semi-Supervised Learning with Sharper Edges
HyunJung (Helen) Shin, College of Medicine, Nicholas Jeremy Hill, Gunnar Rätsch

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

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

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

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

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

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

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

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

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

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

To Select or To Weigh: A Comparative Study of Model Selection and Model Weighing for SPODE Ensembles
Ying Yang, Geoff Webb, Jesus Cerquides, Kevin Korb, Janice Boughton, Kai Ming Ting

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

ECML Short Papers


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

Case-based Label Ranking
Klaus Brinker, Eyke Hüllermeier

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

Making Good Probability Estimates for Regression
Michael Carney, Pádraig Cunningham

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

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

Efficient Inference in Large Conditional Random Fields
Trevor Cohn

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

Cost Sensitive Decision Tree Learning for Forensic Classification
Jason Davis, Jungwoo Ha, Chris Rossbach, Hany Ramadan, Emmett Witchel

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

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

Reinforcement Learning for CMDPs and MDPs with a Constrained Probability of Constraint Violation
Peter Geibel

Efficient Non-Linear Control through Neuroevolution
Faustino Gomez, Jürgen Schmidhuber, Risto Miikkulainen

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

On Testing the Missing at Random Assumption
Manfred Jaeger

B-Matching for Spectral Clustering
Tony Jebara, Vlad Shchogolev

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

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

Classification with Support Hyperplanes
Georgi Nalbantov, Jan Bioch, Patrick Groenen

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

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

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

Scaling Model-based Average-reward Reinforcement Learning for Product Delivery
Scott Proper, Prasad Tadepalli

Robust Probabilistic Calibration
Stefan Rüping

Missing Data in Kernel PCA
Guido Sanguinetti, Neil Lawrence

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

Efficient Large Scale Linear Programming Support Vector Machines
Suvrit Sra

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

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

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

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

Bagging using Statistical Queries
Anneleen Van Assche, Hendrik Blockeel

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

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

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

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

PKDD Full Papers


SD-Map - A Fast Algorithm for Exhaustive Subgroup Discovery
Martin Atzmueller, Frank Puppe

Decision Trees for Hierarchical Multilabel Classification: A Case Study in Functional Genomics
Hendrik Blockeel, Leander Schietgat, Jan Struyf, Saso Dzeroski, Amanda Clare

Clustering Scientific Literature using Sparse Citation Graph Analysis
Levent Bolelli, Seyda Ertekin, C. Lee Giles

VOGUE: A Novel Variable Order-Gap State Machine for Modeling Sequences
Bouchra Bouqata, Christopher Carothers, Boleslaw Szymanski, Mohammed Zaki

Don't Be Afraid of Simpler Patterns
Björn Bringmann, Albrecht Zimmermann, Luc De Raedt, Siegfried Nijssen

An Adaptive Prequential Learning Framework for Bayesian Network Classifiers
Gladys Castillo, Joăo Gama

Adaptive Active Classification of Cell Assay Images
Nicolas Cebron, Michael R. Berthold

Learning Parameters in Entity-relationship Graphs from Ranking Preferences
Soumen Chakrabarti, Alekh Agarwal

Detecting Fraudulent Personalities in Networks of Online Auctioneers
Duen Horng Chau, Shashank Pandit, Christos Faloutsos

Measuring Constraint-Set Utility for Partitional Clustering Algorithms
Ian Davidson, Kiri Wagstaff, Sugato Basu

Discovery of Interesting Regions in Spatial Data Sets Using Supervised Clustering
Christoph Eick, Banafsheh Vaezian, Dan Jiang, Jing Wang

Optimal String Mining under Frequency Constraints
Johannes Fischer, Volker Heun, Stefan Kramer

k-Anonymous Decision Tree Induction
Arik Friedman, Assaf Schuster, Ran Wolff

Closed Sets for Labeled Data
Gemma Garriga, Petra Kralj, Nada Lavrac

Finding Trees from Unordered 0-1 Data
Hannes Heikinheimo, Heikki Mannila, Jouni Seppänen

Web Communities Identification from Random Walks
Jiayuan Huang, Tingshao Zhu, Dale Schuurmans

Information Marginalization on Subgraphs
Jiayuan Huang, Tingshao Zhu, Russell Greiner, Dale Schuurmans, Dengyong Zhou

Why does Subsequence Time-Series Clustering Produce Sine Waves?
Tsuyoshi Ide

Transductive Learning for Text Classification using Explicit Knowledge Models
Georgiana Ifrim, Gerhard Weikum

Exploring Multiple Communities with Kernel-Based Link Analysis
Takahiko Ito, Masashi Shimbo, Daichi Mochihashi, Yuji Matsumoto

Distribution Rules with Numeric Attributes of Interest
Alípio M. Jorge, Paulo J. Azevedo, Fernando Pereira

Tractable Models for Information Diffusion in Social Networks
Masahiro Kimura, Kazumi Saito

Efficient Spatial Classification using Decoupled Conditional Random Fields
Chi-Hoon Lee, Russell Greiner, Osmar Zaiane

Group SAX: Extending the Notion of Contrast Sets to Time Series and Multimedia Data
Jessica Lin, Eamonn Keogh

An Attacker's View of Distance Preserving Maps For Privacy Preserving Data Mining
Kun Liu, Chris Giannella, Hillol Kargupta

A Scalable Distributed Stream Mining System for Highway Traffic Data
Ying Liu, Alok Choudhary, Jianhong Zhou, Ashfaq Khokhar

K-Landmarks: Distributed Dimensionality Reduction for Clustering Quality Maintenance
Panagis Magdalinos, Christos Doulkeridis, Michalis Vazirgiannis

The Discrete Basis Problem
Pauli Miettinen, Taneli Mielikäinen, Aristides Gionis, Gautam Das, Heikki Mannila

Evaluation of Summarization Schemes for Learning in Streams
Alec Pawling, Nitesh Chawla, Amitabh Chaudhary

Efficient Mining of Correlation Patterns in Spatial Point Data
Marko Salmenkivi

Improving Functional Modularity in Protein-Protein Interactions Graphs Using Hub-induced Subgraphs
Duygu Ucar, Sitaram Asur, Umit Catalyurek, Srinivasan Parthasarathy

Refining Aggregate Conditions in Relational Learning
Celine Vens, Jan Ramon, Hendrik Blockeel

Measuring to Fit: Virtual Tailoring through Cluster Analysis and Classification
Herna Viktor, Eric Paquet, Hongyu Guo

RIVA: Indexing and Visualization of High-Dimensional Data via Dimension Reorderings
Michail Vlachos, Spiros Papadimitriou, Zografoula Vagena, Philip Yu

Distributed Subgroup Discovery
Michael Wurst, Martin Scholz

Network Flow for Collaborative Ranking
Ziming Zhuang, Silviu Cucerzan, C. Lee Giles

PKDD Short Papers


Finding Hierarchies of Subspace Clusters
Elke Achtert, Christian Böhm, Hans-Peter Kriegel, Peer Kröger, Ina Müller-Gorman, Arthur Zimek

Integrating Pattern Mining in Relational Databases
Toon Calders, Bart Goethals, Adriana Prado

Discovering Patterns In Real-valued Time Series
Joe Catalano, Tom Armstrong, Tim Oates

Classification of Dementia Types from Cognitive Profiles Data
Giorgio Corani, Chris Edgar, Isabelle Marshall, Keith Wesnes, Marco Zaffalon

When Efficient Model Averaging Out-Performs Boosting and Bagging
Ian Davidson, Wei Fan

Peak-Jumping Frequent Item Set Mining Algorithms
Nele Dexters, Paul W. Purdom, Dirk Van Gucht

Autonomous Visualization
Khalid El-Arini, Andrew Moore, Ting Liu

Naive Bayes for Text Classification with Unbalanced Classes
Eibe Frank, Remco Bouckaert

Knowledge-Conscious Exploratory Data Clustering
Amol Ghoting, Srinivasan Parthasarathy

On the Lower Bound of Reconstruction Error for Spectral Filtering Based Privacy Preserving Data Mining
Songtao Guo, Xintao Wu, Yingjiu Li

Frequent Pattern Discovery without Binarization: Mining Attribute Profiles
Attila Gyenesei, Ralph Schlapbach, Etzard Stolte, Ulrich Wagner

Efficient Name Disambiguation for Large-Scale Databases
Jian Huang, Seyda Ertekin, C. Lee Giles

Adaptive Segmentation-Based Symbolic Representations of Time Series for Better Modeling and Lower Bounding Distance Measures
Bernard Hugueney

Feature Generation for Sequences: An Application to Splice Site Prediction
Rezarta Islamaj, Lise Getoor, W. John Wilbur

Discovering Image-Text Associations for Cross-Media Web Information Fusion
Tao Jiang, Ah-Hwee Tan

Mining Sequences of Temporal Intervals
Steffen Kempe, Jochen Hipp

Pattern Teams
Arno Knobbe, Eric Ho

Compression picks Item Sets that Matter
Matthijs van Leeuwen, Jilles Vreeken, Arno Siebes

Discovering Overlapping Communities of Named Entities
Xin Li, Bing Liu, Philip Yu

Closed Non-Derivable Itemsets
Juho Muhonen, Hannu Toivonen

Learning a Distance Metric for Object Identification without Human Supervision
Satoshi Oyama, Katsumi Tanaka

Towards Association Rules with Hidden Variables
Ricardo Silva, Richard Scheines

A Data Mining Approach to the Joint Evaluation of Field and Manufacturing Data in Automotive Industry
Christian Manuel Strobel, Tomas Hrycej

Incremental Aspect Models for Mining Document Streams
Arun Surendran, Suvrit Sra

Learning Approximate MRFs from Large Transaction Data
Chao Wang, Srinivasan Parthasarathy

Similarity Search for Multi-dimensional NMR-Spectra of Natural Products
Karina Wolfram, Andrea Porzel, Alexander Hinneburg

Photo by Land Berlin/Thie