Accepted Papers
To appear in Machine Learning Journal
- A Collaborative Filtering Framework Based on both Local User Similarity and Global User Similarity
Heng Luo, Changyong Niu, Ruimin Shen, Carsten Ullrich
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- Improving Maximum Margin Matrix Factorization
Markus Weimer, Alexandros Karatzoglou, Alex Smola
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- Incremental Exemplar Learning Schemes for Classification on Embedded Devices
Ankur Jain, Daniel Nikovski
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- A Critical Analysis of Variants of the AUC
Stijn Vanderlooy, Eyke Huellermeier
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- Rollout Sampling Approximate Policy Iteration
Christos Dimitrakakis, Michail G. Lagoudakis
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- Large Margin vs. Large Volume in Transductive
Ran El-Yaniv, Dmitry Pechyony, Vladimir Vapnik
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- New Closed-form Bounds on the Partition Function
Krishnamurthy Dvijotham, Soumen Chakrabarti, Subhasis Chaudhuri
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To appear in Data Mining and Knowledge Discovery Journal
- Two heads better than one: Pattern Discovery in Time-evolving Multi-Aspect Data
Jimeng Sun, Tina Eliassi-Rad, Charalampos E. Tsourakakis, Evan Hoke, Christos Faloutsos
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- Adequate Condensed Representations of Patterns
Arnaud Soulet, Bruno Cremilleux
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- A Space Efficient Solution to the Frequent String Mining Problem for Many Databases
Adrian Kugel, Enno Ohlebusch
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- The Boolean Column and Column-Row Matrix Decompositions
Pauli Miettinen
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- Finding Reliable Subgraphs from Large Probabilistic Graphs
Petteri Hintsanen, Hannu Toivonen
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- SkyGraph: An Algorithm for Important Subgraph Discovery in Relational Graphs
Apostolos Papadopoulos, Apostolos Lyritsis, Yannis Manolopoulos
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- Mining Conjunctive Sequential Patterns
Chedy Raissi, Toon Calders, Pascal Poncelet
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To appear in LNAI proceedings
- Unsupervised Riemannian Clustering of Probability Density Functions
Alvina Goh, René Vidal
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- A Projection-Based Framework for Classifier Performance Evaluation
Nathalie Japkowicz, Pritika Sanghi, Peter Tischer
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- Pool-based Agnostic Experiment Design in Linear Regression
Masashi Sugiyama, Shinichi Nakajima
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- Semi-Supervised Discriminant Analysis via CCCP
Yu Zhang, Dit-Yan Yeung
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- StreamKrimp: Detecting Change in Data Streams
Matthijs van Leeuwen, Arno Siebes
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- Exceptional Model Mining
Dennis Leman, Ad Feelders, Arno Knobbe
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- Actively Transfer Domain Knowledge
Xiaoxiao Shi, Wei Fan, Jiangtao Ren
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- Minimum-Size Bases of Association Rules
José L Balcázar
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- Learning to Predict One or More Ranks in Ordinal Regression Tasks
Jaime Alonso, Juan José Del Coz, Jorge Díez, Oscar Luaces, Antonio Bahamonde
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- Catenary Support Vector Machines
Kin Fai Kan, Christian R. Shelton
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- An Algorithm for Transfer Learning in a Heterogeneous Environment
Andreas Argyriou, Andreas Maurer, Massimiliano Pontil
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- Ranking the Uniformity of Interval Pairs
Jussi Kujala, Tapio Elomaa
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- Exact and Approximate Inference for Annotating Graphs with Structural SVMs
Thoralf Klein, Ulf Brefeld, Tobias Scheffer
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- Distortion-Free Nonlinear Dimensionality Reduction
Yangqing Jia, Zheng Wang, Changshui Zhang
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- A Genetic Algorithm for Text Classification Rule Induction
Adriana Pietramala, Veronica L. Policicchio, Pasquale Rullo, Inderbir Sidhu
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- Parameter Learning in Probabilistic Databases: A Least Squares Approach
Bernd Gutmann, Angelika Kimmig, Kristian Kersting, Luc De Raedt
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- A Fast Method for Training Linear SVM in the Primal
Trinh-Minh-Tri Do, Thierry Artieres
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- Distribution-free Learning of Bayesian Network Structure
Xiaohai Sun
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- A Joint Topic and Perspective Model for Ideological Discourse
Wei-Hao Lin, Eric Xing, Alexander Hauptmann
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- Estimating Sales Opportunity using Similarity-based Methods
Sholom Weiss, Nitin Indurkhya
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- Semi-Supervised Boosting for Multi-Class Classification
Hamed Valizadegan, Rong Jin, Anil K. Jain
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- Hierarchical, Parameter-Free Community Discovery
Spiros Papadimitriou, Jimeng Sun, Philip S. Yu, Christos Faloutsos
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- Hierarchical Distance-based Conceptual Clustering
Ana Maria Funes, Cesar Ferri, Jose Hernandez-Orallo, Maria Jose Ramirez-Quintana
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- Decomposable Families of Itemsets
Nikolaj Tatti, Hannes Heikinheimo
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- Scalable Feature Selection for Multi-Class Problems
Boris Chidlovskii, Loïc Lecerf
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- Effective Pruning Techniques for Mining Quasi-cliques
Guimei Liu, Limsoon Wong
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- Tight Optimistic Estimates for Fast Subgroup Discovery
Henrik Grosskreutz, Stefan Ruping, Stefan Wrobel
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- Improving k-Nearest Neighbour Classification with Distance Functions based on Receiver Operating Characteristics
Md. Rafiul Hassan, M. Maruf Hossain, James Bailey, Kotagiri Ramamohanarao
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- Mining Edge-Weighted Call Graphs to Localise Software Bugs
Frank Eichinger, Klemens Böhm, Matthias Huber
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- Robust Feature Selection using Ensemble Feature Selection Techniques
Yvan Saeys, Thomas Abeel, Yves Van de Peer
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- State-Dependent Exploration for Policy Gradient Methods
Thomas Rückstiess, Martin Felder, Jürgen Schmidhuber
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- Improving Classification with Pairwise Constraints: A Margin-based Approach
Nam Nguyen, Rich Caruana
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- Transferred Dimensionality Reduction
Zheng Wang, Yangqiu Song, Changshui Zhang
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- Sequence Labelling SVMs Trained in One Pass
Antoine Bordes, Nicolas Usunier, Leon Bottou
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- Learning Bidirectional Similarity for Collaborative Filtering
Bin Cao, Jian-Tao Sun, Jianmin Wu, Qiang Yang, Zheng Chen
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- Semi-Supervised Laplacian Regularization of Kernel Canonical Correlation Analysis
Matthew B. Blaschko, Christoph H. Lampert, Arthur Gretton
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- Combining Classifiers through Triplet-based Belief Functions
Yaxin Bi, Shengli Wu, Xuhui Shen, Pan Xiong
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- Transferring Instances for Model-Based Reinforcement Learning
Matthew E. Taylor, Nicholas K. Jong, Peter Stone
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- Nearest Neighbour Classification with Monotonicity Constraints
Wouter Duivesteijn, Ad Feelders
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- Mining Frequent Connected Subgraphs Reducing the Number of Candidates
Andrés Gago Alonso, José E. Medina Pagola, J. Ariel Carrasco-Ochoa, J. Fco. Martínez-Trinidad
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- A Joint Segmenting and Labeling Approach for Chinese Lexical Analysis
Xinhao Wang, Jiazhong Nie, Dingsheng Luo, Xihong Wu
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- A Novel Scalable and Data Efficient Feature Subset Selection Algorithm
Sergio Rodrigues de Morais, Alex Aussem
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- On the equivalence of the SMO and MDM Algorithms for SVM Training
Jose R. Dorronsoro, Alvaro Barbero, Jorge Lopez
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- A Case Study in Sequential Pattern Mining for IT-Operational Risk
Valerio Grossi, Andrea Romei, Salvatore Ruggieri
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- Multiagent Reinforcement Learning for Urban Traffic Control using Coordination Graphs
Lior Kuyer, Shimon Whiteson, Bram Bakker, Nikos Vlassis
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- Credal Model Averaging: an Extension of Bayesian Model Averaging to Imprecise Probabilities
Giorgio Corani, Marco Zaffalon
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- Semi-supervised Classification from Discriminative Random Walks
Jerome Callut, Kevin Francoisse, Marco Saerens, Pierre Dupont
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- Modeling Transfer Relationships Between Learning Tasks for Improved Inductive Transfer
Eric Eaton, Marie desJardins, Terran Lane
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- Large-Scale Clustering through Functional Embedding
Frederic Ratle, Jason Weston, Matthew L. Miller
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- Multiple Manifold Learning Framework based on Hierarchical Mixture Density Model
Xiaoxia Wang, Peter Tino, Mark A. Fardal
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- Fitted Natural Actor-Critic: A New Algorithm for Continuous State-Action MDPs
Francisco S. Melo, Manuel C. Lopes
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- Efficient Pairwise Multilabel Classification for Large-Scale Problems in the Legal Domain
Eneldo Loza Mencía, Johannes Fürnkranz
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- A New Natural Policy Gradient by Stationary Distribution Metric
Tetsuro Morimura, Eiji Uchibe, Junichiro Yoshimoto, Kenji Doya
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- Continuous Time Bayesian Networks for Host Level Network Intrusion Detection
Jing Xu, Christian R. Shelton
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- A Fast Algorithm to Find Overlapping Communities in Networks
Steve Gregory
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- Mixed Bregman Clustering with Approximation Guarantees
Richard Nock, Panu Luosto, Jyrki Kivinen
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- Effective Visualization of Information Diffusion Process over Complex Networks
Kazumi Saito, Masahiro Kimura, Hiroshi Motoda
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- Bootstrapping Information Extraction from Semi-structured Web Pages
Andrew Carlson, Charles Schafer
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- Assessing Nonlinear Granger Causality from Multivariate Time Series
Xiaohai Sun
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- Data Streaming with Affinity Propagation
Xiangliang Zhang, Cyril Furtlehner, Michele Sebag
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- Metric Learning: A Support Vector Approach
Nam Nguyen, Yunsong Guo
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- Watch, Listen & Learn: Co-training on Captioned Images and Videos
Sonal Gupta, Joohyun Kim, Kristen Grauman, Raymond Mooney
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- Clustering Distributed Sensor Data Streams
Pedro Rodrigues-Pereira, João Gama, Luís Lopes
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- Client-Friendly Classification over Random Hyperplane Hashes
Shyamsundar Rajaram, Martin Scholz
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- An Improved Multi-task Learning Approach with Applications in Medical Diagnosis
Jinbo Bi, Tao Xiong, Shipeng Yu, Murat Dundar, Bharat Rao
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- TOPTMH: Topology Predictor for Transmembrane Alpha Helices
Rezwan Ahmed, Huzefa Rangwala, George Karypis
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- Online Multiagent Learning against Memory Bounded Adversaries
Doran Chakraborty, Peter Stone
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- Towards Machine Learning of Grammars and Compilers of Programming Languages
Katsuhiko Nakamura, Keita Imada
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- Clustering via Local Regression
Jun Sun, Zhiyong Shen, Hui Li, Yidong Shen
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- Proper Model Selection with Significance Test
Jin Huang, Charles X. Ling, Harry Zhang, Stan Matwin
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- Support Vector Machines, Data Reduction, and Approximate Kernel Matrices
XuanLong Nguyen, Ling Huang, Anthony D. Joseph
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- A Simple Model for Sequences of Relational State Descriptions
Ingo Thon, Niels Landwehr, Luc De Raedt
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- Cascade RSVM in Peer-to-Peer Networks
Hock Hee Ang, Vivekanand Gopalkrishnan, Steven C. H. Hoi, Wee Keong Ng
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- Learning Decision Trees for Unbalanced Data
David A. Cieslak, Nitesh V. Chawla
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- Classification of Multi-Labeled Data: A Generative Approach
Andreas P. Streich, Joachim M. Buhmann
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- Extracting Semantic Networks from Text via Relational Clustering
Stanley Kok, Pedro Domingos
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- One-class Classification by Combining Density and Class Probability Estimation
Kathryn Hempstalk, Eibe Frank, Ian H. Witten
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- Learning MDP Action Models via Discrete Mixture Trees
Michael Wynkoop, Thomas Dietterich
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- A Unified View of Matrix Factorization Models
Ajit P. Singh, Geoffrey J. Gordon
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- Kernel-Based Inductive Transfer
Ulrich Rückert, Stefan Kramer
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- Nonstationary Gaussian Process Regression using Point Estimates of Local Smoothness
Christian Plagemann, Kristian Kersting, Wolfram Burgard
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- Parallel Spectral Clustering
Yangqiu Song, Wen-Yen Chen, Hongjie Bai, Chih-Jen Lin, Edward Y. Chang
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- Learning with $L_{q<1}$ vs $L_1$-norm regularisation with exponentially many irrelevant features
Ata Kaban, Robert Durrant
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- Efficient Frequent Connected Subgraph Mining in Graphs of Bounded Treewidth
Tamas Horvath, Jan Ramon
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- Online Manifold Regularization: A New Learning Setting and Empirical Study
Andrew B. Goldberg, Ming Li, Xiaojin Zhu
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