Accepted Papers

To appear in Machine Learning Journal

  • Cost-sensitive learning based on Bregman divergences
    Raúl Santos-Rodríguez, Rocío Alaiz-Rodríguez, Alicia Guerrero-Curieses, Jesús Cid-Sueiro
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  • On Structured Output Training: Hard Cases and an Efficient Alternative
    Thomas Gärtner, Shankar Vembu
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  • A Self-Training Approach to Cost Sensitive Uncertainty Sampling
    Alexander Liu, Goo Jun, Joydeep Ghosh
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  • Sparse Kernel SVMs via Cutting-Plane Training
    Thorsten Joachims, Chun-Nam Yu
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  • Combining Instance-Based Learning and Logistic Regression for Multi-Label Classification
    Weiwei Cheng, Eyke Huellermeier
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  • Hybrid Least-Squares Algorithms for Approximate Policy Evaluation
    Jeffrey Johns, Marek Petrik, Sridhar Mahadevan
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  • Learning Multi-linear Representations of Distributions for Efficient Inference
    Dan Roth, Rajhans Samdani
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To appear in Data Mining and Knowledge Discovery Journal

  • On Subgroup Discovery in Numerical Domains
    Henrik Grosskreutz, Stefan Rüping
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  • Harnessing the Strengths of Anytime Algorithms for Constant Data Streams
    Philipp Kranen, Thomas Seidl
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  • RTG: A Recursive Realistic Graph Generator using Random Typing
    Leman Akoglu, Christos Faloutsos
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  • A Fast Ensemble Pruning Algorithm Based on Pattern Mining Process
    Qiang-Li Zhao, Yan-Huang Jiang, Ming Xu
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  • Taxonomy-driven lumping for sequence mining
    Francesco Bonchi, Carlos Castillo, Debora Donato, Aristides Gionis
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  • Identifying the Components
    Matthijs van Leeuwen, Jilles Vreeken, Arno Siebes
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  • Two-Way Analysis of High-Dimensional Collinear Data
    Ilkka Huopaniemi,Tommi Suvitaival, Janne Nikkila, Matej Oresic, Samuel Kaski
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To appear in LNAI proceedings

  • Active Learning for Reward Estimation in Inverse Reinforcement Learning
    Manuel Lopes, Francisco Melo, Luis Montesano
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  • Active and Semi-supervised Data Domain Description
    Nico Goernitz, Marius Kloft, Ulf Brefeld
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  • Feature Selection for Density Level-Sets
    Marius Kloft, Shinichi Nakajima, Ulf Brefeld
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  • Leveraging Higher Order Dependencies Between Features for Text Classification
    Murat C. Ganiz, Nikita I. Lytkin, William M. Pottenger
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  • Efficient Sample Reuse in EM-based Policy Search
    Hirotaka Hachiya, Jan Peters, Masashi Sugiyama
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  • Conference Mining via Generalized Topic Modeling
    Ali Daud, Juanzi Li, Lizhu Zhou, Faqir Muhammad
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  • Relaxed Transfer of Different Classes via Spectral Partition
    Xiaoxiao Shi,Wei Fan, Qiang Yang, Jiangtao Ren
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  • Universal Learning over Related Distributions and Adaptive Graph Transduction
    Erheng Zhong, Wei Fan, Jing Peng, Olivier Verscheure, Jiangtao Ren
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  • Reconstructing Data Perturbed by Random Projections when the Mixing Matrix is Known
    Yingpeng Sang, Hong Shen, Hui Tian
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  • Enhancing the Performance of Centroid Classifier by ECOC and Model-Refinement
    Songbo Tan, Gaowei Wu, Xueqi Cheng
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  • Transductive Classification via Dual Regularization
    Quanquan Gu, Jie Zhou
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  • Non-Redundant Subgroup Discovery Using a Closure System
    Mario Boley, Henrik Grosskreutz
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  • Kernel-based Copula Processes
    Sebastian Jaimungal, Eddie K. H. Ng
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  • Max-Margin Weight Learning for Markov Logic Networks
    Tuyen N. Huynh, Raymond J. Mooney
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  • Learning to Disambiguate Search Queries from Short Sessions
    Lilyana Mihalkova, Raymond Mooney
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  • Semi-supervised Document Clustering with Simultaneous Text Representation and Categorization
    Yanhua Chen, Lijun Wang, Ming Dong
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  • A Condensed Representation of Itemsets for Analyzing their Evolution over Time
    Mirko Boettcher, Martin Spott, Rudolf Kruse
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  • Adaptive XML Tree Classification on Evolving Data Streams
    Albert Bifet, Ricard Gavaldà
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  • Feature Selection for Value Function Approximation Using Bayesian Model Selection
    Tobias Jung, Peter Stone
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  • Subspace Regularization: a New Semi-Supervised Learning Method
    Yan-Ming Zhang, Xinwen Hou, Shiming Xiang, Cheng-Lin Liu
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  • An \ell_1 Regularization Framework for Optimal Rule Combination
    Yanjun Han, Jue Wang
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  • Feature Selection by Transfer Learning with Linear Regularized Models
    Thibault Helleputte, Pierre Dupont
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  • Boosting Active Learning to Optimality: a Tractable Monte-Carlo, Billiard-based Algorithm
    Philippe Rolet, Michèle Sebag, Olivier Teytaud
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  • One Graph is Worth a Thousand Logs: Uncovering Hidden Structures in Massive System Event Logs
    Ira Cohen, Michal Aharon, Gilad Barash, Eli Mordechai
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  • A Flexible and Efficient Algorithm for Regularized Fisher Discriminant Analysis
    Zhihua Zhang, Guang Dai, Michael Jordan
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  • Optimal Online Learning Procedures for Model-Free Policy Evaluation
    Tsuyoshi Ueno, Shin-ichi Maeda, Motoaki Kawanabe, Shin Ishii
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  • Minimum Free Energy Principle for Constraint-Based Learning Bayesian Networks
    Takashi Isozaki, Maomi Ueno
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  • Considering unseen states as impossible in Factored Reinforcement Learning
    Olga Kozlova, Olivier Sigaud, Pierre-Henri Wuillemin, Christophe Meyer
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  • Classifier Chains for Multi-label Classification
    Jesse Read, Bernhard Pfahringer, Geoffrey Holmes, Eibe Frank
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  • Mining Peculiar Compositions of Frequent Substrings from Sparse Text Data Using Background Texts
    Daisuke Ikeda, Einoshin Suzuki
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  • Soft Margin Trees
    Jorge Díez, Juan José del Coz, Antonio Bahamonde, Oscar Luaces
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  • Latent Dirichlet Bayesian Co-Clustering
    Pu Wang, Carlotta Domeniconi, Kathryn Blackmond Laskey
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  • MACs: Multi-Attribute Co-Clusters with High Correlation Information
    Kelvin Sim, Vivekanand Gopalkrishnan, Hon Nian Chua, See-Kiong Ng
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  • Efficient Pruning Schemes for Distance-Based Outlier Detection
    Hoang Vu Nguyen, Vivekanand Gopalkrishnan
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  • Mining Databases to Mine Queries Faster
    Arno Siebes, Diyah Puspitaningrum
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  • Heteroscedastic Probabilistic Linear Discriminant Analysis with Semi-Supervised Extension
    Yu Zhang, Dit-Yan Yeung
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  • Communication-efficient Classification in P2P Networks
    Hock Hee Ang, Vivekanand Gopalkrishnan, Wee Keong Ng, Hoi Chu Hong
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  • Semi-Supervised Multi-Task Regression
    Yu Zhang, Dit-Yan Yeung
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  • Statistical Relational Learning with Formal Ontologies
    Achim Rettinger, Matthias Nickles,Volker Tresp
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  • The Feature Importance Ranking Measure
    Alexander Zien, Nicole Krämer, Sören Sonnenburg, Gunnar Rätsch
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  • Efficient Decoding of Ternary Error-Correcting Output Codes for Multiclass Classification
    Sang-Hyeun Park, Johannes Fürnkranz
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  • Integrating Logical Reasoning and Probabilistic Chain Graphs
    Arjen Hommersom, Nivea Ferreira, Peter Lucas
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  • A Matrix Factorization Approach for Integrating Multiple Data Views
    Derek Greene, Pádraig Cunningham
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  • Mining Graph Evolution Rules
    Michele Berlingerio, Francesco Bonchi, Björn Bringmann, Aristides Gionis
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  • PLSI: the True Fisher Kernel and Beyond
    Jean-Cedric Chappelier, Emmanuel Eckard
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  • Efficient Multi-Start Strategies for Local Search Algorithms
    Levente Kocsis, András György
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  • Inference and Validation of Networks
    Ilias Flaounas, Marco Turchi, Tijl De Bie, Nello Cristianini
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  • Learning Preferences with Hidden Common Cause Relations
    Kristian Kersting, Zhao Xu
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  • A Convex Method for Locating Regions of Interest with Multi-Instance Learning
    Yu-Feng Li, James T. Kwok, Ivor W. Tsang, Zhi-Hua Zhou
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  • Identifying the Original Contribution of a Document via Language Modeling
    Benyah Shaparenko, Thorsten Joachims
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  • On Feature Selection, Bias-Variance, and Bagging
    M. Arthur Munson, Rich Caruana
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  • Dependency Tree Kernels for Relation Extraction from Natural Language Text
    Frank Reichartz, Hannes Korte, Gerhard Paass
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  • Latent Dirichlet Allocation for Automatic Document Categorization
    Jácint Szabó, István Bíró
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  • Relevance Grounding for Planning in Relational Domains
    Tobias Lang, Marc Toussaint
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  • Multi-Task Feature Selection Using the Multiple Inclusion Criterion (MIC)
    Paramveer S. Dhillon, Brian Tomasik, Dean Foster, Lyle Ungar
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  • The Model of Most Informative Patterns and its Application to Knowledge Extraction from Graph Databases
    Frédéric Pennerath, Amedeo Napoli
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  • Simulated Iterative Classification: A New Learning Procedure for Graph Labeling
    Francis Maes, Stephane Peters, Ludovic Denoyer, Patrick Gallinari
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  • Feature Weighting Using Margin and Radius Based Error Bound Optimization in SVMs
    Huyen Thi Thanh Do, Alexandros Kalousis, Melanie Hilario
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  • Parameter-free Hierarchical Co-Clustering by $n$-Ary Splits
    Dino Ienco, Ruggero G. Pensa, Rosa Meo
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  • Margin and Radius Based Multiple Kernel Learning
    Huyen Thi Thanh Do, Alexandros Kalousis, Adam Woznica, Melanie Hilario
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  • Neural Networks for State Evaluation in General Game Playing
    Daniel Michulke, Michael Thielscher

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  • New Regularized Algorithms for Transducitve Learning
    Partha Pratim Talukdar, Koby Crammer
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  • Evaluation Measures for Multi-Class Subgroup Discovery
    Tarek Abudawood, Peter Flach
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  • K-Subspace Clustering
    Dingding Wang, Chris Ding, Tao Li
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  • Kernel Polytope Faces Pursuit
    Tom Diethe, Zakria Hussain
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  • Compositional Models for Reinforcement Learning
    Nicholas K. Jong, Peter Stone
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  • Parallel Subspace Sampling for Particle Filtering in Dynamic Bayesian Networks
    Eva Besada-Portas, Sergey M. Plis, Jesus M. de la Cruz, Terran Lane
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  • Decomposition Algorithms for Training Large-scale Semiparametric Support Vector Machines
    Sangkyun Lee, Stephen Wright
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  • Within-network Classification Using Local Structure Similarity
    Christian Desrosiers, George Karypis
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  • Topic Significance Ranking of LDA Generative Models
    Loulwah AlSumait, Daniel Barbara, James E. Gentle, Carlotta Domeniconi
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  • Mining Spatial Co-location Patterns with Dynamic Neighborhood Constraint
    Feng Qian, Qinming He, Jiangfeng He
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  • A Generalization of Forward-backward Algorithm
    Ai Azuma, Yuji Matsumoto
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  • Bi-directional Joint Inference for Entity Resolution and Segmentation Using Imperatively-Defined Factor Graphs
    Sameer Singh, Karl Schultz, Andrew McCallum
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  • Binary Decomposition Methods for Multipartite Ranking
    Johannes Fuernkranz, Eyke Huellermeier, Stijn Vanderlooy
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  • The Sensitivity of Latent Dirichlet Allocation for Information Retrieval
    Laurence Park, Kotagiri Ramamohanarao
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  • A Generic Approach to Topic Models
    Gregor Heinrich
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  • Stable and Accurate Feature Selection
    Gokhan Gulgezen, Zehra Cataltepe, Lei Yu
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  • Capacity Control for Partially Ordered Feature Sets
    Ulrich Rückert
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  • Empirical Study of Relational Learning Algorithms in the Phase Transition Framework
    Erick Alphonse, Aomar Osmani
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  • Integrating Novel Class Detection with Classification for Concept-Drifting Data Streams
    Mohammad M Masud, Jing Gao, Latifur Khan, Jiawei Han, Bhavani Thuraisingham
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  • Acyclic Causality Discovery with Additive Noise: An Information-Theoretical Perspective
    Kun Zhang, Aapo Hyvärinen
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  • Syntactic Structural Kernels for Natural Language Interfaces to Databases
    Alessandra Giordani, Alessandro Moschitti
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  • Learning the difference between partially observable dynamical systems
    Sami Zhioua, Josee Desharnais, Francois Laviolette, Doina Precup
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  • Debt Detection in Social Security by Sequence Classification Using Both Positive and Negative Patterns
    Yanchang Zhao, Huaifeng Zhang, Shanshan Wu, Jian Pei, Longbing Cao, Chengqi Zhang, Hans Bohlscheid
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  • Protein Identification from Tandem Mass Spectra with Probabilistic Language Modeling
    Yiming Yang, Abhay Harpale, Subramaniam Ganapathy
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  • Applying Electromagnetic Field Theory Concepts to Clustering with Constraints
    Huseyin Hakkoymaz, Georgios Chatzimilioudis, Dimitrios Gunopulos, Heikki Mannila
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  • Dynamic Factor Graphs for Time Series Modeling
    Piotr Mirowski, Yann LeCun
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  • Graph-based Discrete Differential Geometry for Critical Instance Filtering
    Elena Marchiori
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  • On Discriminative Parameter Learning of Bayesian Network Classifiers
    Franz Pernkopf, Michael Wohlmayr
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  • Kernels for Periodic Time Series Arising in Astronomy
    Gabriel Wachman, Roni Khardon, Pavlos Protopapas, Charles R. Alcock
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  • Variational Graph Embedding for Globally and Locally Consistent Feature Extraction
    Shuang-Hong Yang, Hongyuan Zha, S.Kevin Zhou, Bao-Gang Hu
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