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ECML Full Papers |
ECML Short Papers |
PKDD Full Papers |
PKDD Short Papers
ECML Full Papers
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Learning in One-Shot Strategic Form Games
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Alon Altman,
Avivit Bercovici-Boden,
Moshe Tennenholtz
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A Selective Sampling Strategy for Label-Ranking
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Massih Amini,
Nicolas Usunier,
François Laviolette,
Alexandre Lacasse,
Patrick Gallinari
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Combinatorial Markov Random Fields
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Ron Bekkerman,
Mehran Sahami,
Erik Learned-Miller
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Learning Stochastic Tree Edit Distance
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Marc Bernard,
Amaury Habrard,
Marc Sebban
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Pertinent Background Knowledge for Learning Protein Grammars
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Christopher H. Bryant,
Daniel C. Fredouille,
Alex Wilson,
Channa K. Jayawickreme,
Steven Jupe,
Simon Topp
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Improving Bayesian Network Structure Search with Random Variable Aggregation Hierarchies
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John Burge,
Terran Lane
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Sequence Discrimination Using Phase-type Distributions
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Jérôme Callut,
Pierre Dupont
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Languages as Hyperplanes: Grammatical Inference with String Kernels
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Alexander Clark,
Christophe Costa Florencio,
Chris Watkins
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Toward Robust Real-World Inference: A New Perspective on Explanation-Based Learning
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Gerald DeJong
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Fisher Kernels for Relational Data
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Uwe Dick,
Kristian Kersting
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Evaluating Misclassifications in Imbalanced Data
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William Elazmeh,
Nathalie Japkowicz,
Stan Matwin
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Improving Control-Knowledge Acquisition for Planning by Active Learning
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Raquel Fuentetaja,
Daniel Borrajo
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Learning Markov Models with Hidten State
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Ricard Gavalda,
Philipp Keller,
Joelle Pineau,
Doina Precup
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A Discriminative Approach for the Retrieval of Images from Text Queries
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David Grangier,
Florent Monay,
Samy Bengio
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TildeCRF: Conditional Random Fields for Logical Sequences
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Bernd Gutmann,
Kristian Kersting
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Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data
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Corneliu Henegar,
Karine Clement,
Jean-Daniel Zucker
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Bayesian Learning of Markov Network Structure
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Aleks Jakulin,
Irina Rish
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Approximate Policy Iteration for Closed-Loop Learning of Visual Tasks
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Sébastien Jodogne,
Cyril Briquet,
Justus H. Piater
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Task-Driven Discretization of the Joint Space of Visual Percepts and Continuous Actions
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Sébastien Jodogne,
Justus H. Piater
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EM Algorithm for Symmetric Causal Independence Models
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Rasa Jugelenaite,
Tom Heskes
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Deconvolutive Clustering of Markov States
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Ata Kaban,
Xin Wang
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Patching Approximate Solutions in Reinforcement Learning
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Min Sub Kim,
William Uther
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Fast Variational Inference for Gaussian Process Models through KL-Correction
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Nathaniel King,
Neil Lawrence
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Bandit Based Monte-Carlo Planning
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Levente Kocsis,
Csaba Szepesvári
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Bayesian Learning with Mixtures of Trees
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Jussi Kollin,
Mikko Koivisto
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Transductive Gaussian Process Regression with Automatic Model Selection
- Quoc V. Le,
Australia
- Alex Smola,
Australia
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Thomas Gärtner,
Yasemin Altun
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Efficient Convolution Kernels for Dependency and Constituent Syntactic Trees
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Alessandro Moschitti
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Why Is Rule Learning Optimistic and How to Correct It
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Martin Mozina,
Janez Demsar,
Jure Zabkar,
Ivan Bratko
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Automatically Evolving Rule Induction Algorithms
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Gisele Pappa,
Alex Freitas
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Bayesian Active Learning for Sensitivity Analysis
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Tobias Pfingsten
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Mixtures of Kikuchi Approximations
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Roberto Santana,
Pedro Larrańaga,
Jose A. Lozano
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Boosting in PN Spaces
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Martin Scholz
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Prioritized Value Iteration for POMDPs
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Guy Shani,
Ronen Brafman,
Solomon Shimony
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Graph Based Semi-Supervised Learning with Sharper Edges
- HyunJung (Helen) Shin,
College of Medicine,
Nicholas Jeremy Hill,
Gunnar Rätsch
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Margin-based Active Learning for Structured Output Spaces
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Kevin Small,
Dan Roth
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Skill Acquisition via Transfer Learning and Advice Taking
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Lisa Torrey,
Jude Shavlik,
Trevor Walker,
Richard Maclin
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Constant Rate Approximate Maximum Margin Algorithms
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Petroula Tsampouka,
John Shawe-Taylor
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Batch Classification with Applications in Computer Aided Diagnosis
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Volkan Vural,
Glenn Fung,
Balaji Krishnapuram,
Jennifer Dy,
Bharat Rao
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Improving the Ranking Performance of Decision Trees
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Bin Wang,
Harry Zhang
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Multiple-Instance Learning via Random Walk
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Dong Wang,
Jianmin Li,
Bo Zhang
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Localized Alternative Cluster Ensembles for Collaborative Structuring
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Michael Wurst,
Katharina Morik,
Ingo Mierswa
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Distributional Features for Text Categorization
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Xiao-Bing Xue,
Zhi-Hua Zhou
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Subspace Metric Ensembles for Semi-supervised Clustering of High Dimensional Data
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Bojun Yan,
Carlotta Domeniconi
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An Adaptive Kernel Method for Semi-Supervised Clustering
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Bojun Yan,
Carlotta Domeniconi
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To Select or To Weigh: A Comparative Study of Model Selection and Model Weighing for SPODE Ensembles
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Ying Yang,
Geoff Webb,
Jesus Cerquides,
Kevin Korb,
Janice Boughton,
Kai Ming Ting
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Ensembles of Nearest Neighbor Forecasts
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Dragomir Yankov,
Dennis DeCoste,
Eamonn Keogh
ECML Short Papers
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Learning Process Models with Missing Data
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Will Bridewell,
Pat Langley,
Steve Racunas,
Stuart Borrett
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Case-based Label Ranking
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Klaus Brinker,
Eyke Hüllermeier
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Cascade Evaluation of Clustering Algorithms
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Laurent Candillier,
Isabelle Tellier,
Fabien Torre,
Olivier Bousquet
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Making Good Probability Estimates for Regression
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Michael Carney,
Pádraig Cunningham
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Fast Spectral Clustering of Data using Sequential Matrix Compression
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Bo Chen,
Bin Gao,
Tie-Yan Liu,
Yu-Fu Chen,
Wei-Ying Ma
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An Information-Theoretic Framework for High-Order Co-Clustering of Heterogeneous Objects
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Antonio Domenico Chiaravalloti,
Gianluigi Greco,
Antonella Guzzo,
Luigi Pontieri
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Efficient Inference in Large Conditional Random Fields
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Trevor Cohn
- A Kernel-Based Approach to Estimating Phase Shifts Between
Irregularly Sampled Time Series: An Application to Gravitational Lenses
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Juan Carlos Cuevas Tello,
Peter Tino,
Somak Raychaudhury
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Cost Sensitive Decision Tree Learning for Forensic Classification
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Jason Davis,
Jungwoo Ha,
Chris Rossbach,
Hany Ramadan,
Emmett Witchel
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The Minimum Volume Covering Ellipsoid Estimation in Kernel-Defined Feature Spaces
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Alexander Dolia,
Tijl De Bie,
Chris Harris,
John Shawe-Taylor,
D. Michael Titterington
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Right of Inference: Nearest Rectangle Learning Revisited
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Byron Gao,
Martin Ester
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Reinforcement Learning for CMDPs and MDPs with a Constrained Probability of Constraint Violation
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Peter Geibel
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Efficient Non-Linear Control through Neuroevolution
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Faustino Gomez,
Jürgen Schmidhuber,
Risto Miikkulainen
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Efficient Prediction-Based Validation for Document Clustering
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Derek Greene,
Pádraig Cunningham
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On Testing the Missing at Random Assumption
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Manfred Jaeger
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B-Matching for Spectral Clustering
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Tony Jebara,
Vlad Shchogolev
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Multi-class Ensemble Based Active Learning
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Christine Körner,
Stefan Wrobel
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Active Learning with Irrelevant Examples
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Dominic Mazzoni,
Kiri Wagstaff,
Michael Burl
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Classification with Support Hyperplanes
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Georgi Nalbantov,
Jan Bioch,
Patrick Groenen
- (Agnostic) PAC Learning Concepts in Higher-order Logic
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Kee Siong Ng
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Evaluating Feature Selection for SVMs in High Dimensions
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Roland Nilsson,
José M. Peńa,
Johan Björkegren,
Jesper Tegnér
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Revisiting Fisher-Kernels for Document Similarities
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Martin Nyffenegger,
Jean-Cédric Chappelier,
Eric Gaussier
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Scaling Model-based Average-reward Reinforcement Learning for Product Delivery
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Scott Proper,
Prasad Tadepalli
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Robust Probabilistic Calibration
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Stefan Rüping
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Missing Data in Kernel PCA
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Guido Sanguinetti,
Neil Lawrence
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Exploiting Extremely Rare Features in Text Categorization
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Péter Schönhofen,
András Benczúr
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Efficient Large Scale Linear Programming Support Vector Machines
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Suvrit Sra
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An Efficient Approximation to Lookahead in Relational Learners
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Jan Struyf,
Jesse Davis,
David Page
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Improvement of Systems Management Policies Using Hybrid Reinforcement Learning
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Gerald Tesauro,
Nicholas Jong,
Rajarshi Das,
Mohamed Bennani
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Diversified SVM Ensembles for Large Data Sets
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Ivor W. Tsang,
Andras Kocsor,
James T. Kwok
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Dynamic Integration with Random Forests
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Alexey Tsymbal,
Mykola Pechenizkiy,
Pádraig Cunningham
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Bagging using Statistical Queries
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Anneleen Van Assche,
Hendrik Blockeel
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Guiding the Search in the NO Region of the Phase Transition Problem with a Partial Subsumption Test
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Samuel Wieczorek,
Gilles Bisson,
Mirta B. Gordon
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Spline Embedding for Nonlinear Dimensionality Reduction
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Shiming Xiang,
Feiping Nie,
Changshui Zhang,
Chunxia Zhang
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Cost-sensitive Learning of SVM for Ranking
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Jun Xu,
Yunbo Cao,
Hang Li,
Yalou Huang
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Variational Bayesian Dirichlet-Multinomial Allocation for Exponential Family Mixtures
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Shipeng Yu,
Kai Yu,
Volker Tresp,
Hans-Peter Kriegel
PKDD Full Papers
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SD-Map - A Fast Algorithm for Exhaustive Subgroup Discovery
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Martin Atzmueller,
Frank Puppe
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Decision Trees for Hierarchical Multilabel Classification: A Case Study in Functional Genomics
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Hendrik Blockeel,
Leander Schietgat,
Jan Struyf,
Saso Dzeroski,
Amanda Clare
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Clustering Scientific Literature using Sparse Citation Graph Analysis
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Levent Bolelli,
Seyda Ertekin,
C. Lee Giles
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VOGUE: A Novel Variable Order-Gap State Machine for Modeling Sequences
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Bouchra Bouqata,
Christopher Carothers,
Boleslaw Szymanski,
Mohammed Zaki
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Don't Be Afraid of Simpler Patterns
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Björn Bringmann,
Albrecht Zimmermann,
Luc De Raedt,
Siegfried Nijssen
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An Adaptive Prequential Learning Framework for Bayesian Network Classifiers
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Gladys Castillo,
Joăo Gama
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Adaptive Active Classification of Cell Assay Images
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Nicolas Cebron,
Michael R. Berthold
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Learning Parameters in Entity-relationship Graphs from Ranking Preferences
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Soumen Chakrabarti,
Alekh Agarwal
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Detecting Fraudulent Personalities in Networks of Online Auctioneers
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Duen Horng Chau,
Shashank Pandit,
Christos Faloutsos
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Measuring Constraint-Set Utility for Partitional Clustering Algorithms
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Ian Davidson,
Kiri Wagstaff,
Sugato Basu
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Discovery of Interesting Regions in Spatial Data Sets Using Supervised Clustering
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Christoph Eick,
Banafsheh Vaezian,
Dan Jiang,
Jing Wang
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Optimal String Mining under Frequency Constraints
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Johannes Fischer,
Volker Heun,
Stefan Kramer
- k-Anonymous Decision Tree Induction
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Arik Friedman,
Assaf Schuster,
Ran Wolff
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Closed Sets for Labeled Data
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Gemma Garriga,
Petra Kralj,
Nada Lavrac
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Finding Trees from Unordered 0-1 Data
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Hannes Heikinheimo,
Heikki Mannila,
Jouni Seppänen
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Web Communities Identification from Random Walks
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Jiayuan Huang,
Tingshao Zhu,
Dale Schuurmans
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Information Marginalization on Subgraphs
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Jiayuan Huang,
Tingshao Zhu,
Russell Greiner,
Dale Schuurmans,
Dengyong Zhou
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Why does Subsequence Time-Series Clustering Produce Sine Waves?
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Tsuyoshi Ide
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Transductive Learning for Text Classification using Explicit Knowledge Models
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Georgiana Ifrim,
Gerhard Weikum
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Exploring Multiple Communities with Kernel-Based Link Analysis
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Takahiko Ito,
Masashi Shimbo,
Daichi Mochihashi,
Yuji Matsumoto
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Distribution Rules with Numeric Attributes of Interest
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Alípio M. Jorge,
Paulo J. Azevedo,
Fernando Pereira
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Tractable Models for Information Diffusion in Social Networks
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Masahiro Kimura,
Kazumi Saito
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Efficient Spatial Classification using Decoupled Conditional Random Fields
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Chi-Hoon Lee,
Russell Greiner,
Osmar Zaiane
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Group SAX: Extending the Notion of Contrast Sets to Time Series and Multimedia Data
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Jessica Lin,
Eamonn Keogh
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An Attacker's View of Distance Preserving Maps For Privacy Preserving Data Mining
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Kun Liu,
Chris Giannella,
Hillol Kargupta
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A Scalable Distributed Stream Mining System for Highway Traffic Data
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Ying Liu,
Alok Choudhary,
Jianhong Zhou,
Ashfaq Khokhar
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K-Landmarks: Distributed Dimensionality Reduction for Clustering Quality Maintenance
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Panagis Magdalinos,
Christos Doulkeridis,
Michalis Vazirgiannis
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The Discrete Basis Problem
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Pauli Miettinen,
Taneli Mielikäinen,
Aristides Gionis,
Gautam Das,
Heikki Mannila
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Evaluation of Summarization Schemes for Learning in Streams
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Alec Pawling,
Nitesh Chawla,
Amitabh Chaudhary
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Efficient Mining of Correlation Patterns in Spatial Point Data
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Marko Salmenkivi
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Improving Functional Modularity in Protein-Protein Interactions Graphs Using Hub-induced Subgraphs
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Duygu Ucar,
Sitaram Asur,
Umit Catalyurek,
Srinivasan Parthasarathy
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Refining Aggregate Conditions in Relational Learning
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Celine Vens,
Jan Ramon,
Hendrik Blockeel
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Measuring to Fit: Virtual Tailoring through Cluster Analysis and Classification
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Herna Viktor,
Eric Paquet,
Hongyu Guo
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RIVA: Indexing and Visualization of High-Dimensional Data via Dimension Reorderings
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Michail Vlachos,
Spiros Papadimitriou,
Zografoula Vagena,
Philip Yu
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Distributed Subgroup Discovery
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Michael Wurst,
Martin Scholz
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Network Flow for Collaborative Ranking
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Ziming Zhuang,
Silviu Cucerzan,
C. Lee Giles
PKDD Short Papers
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Finding Hierarchies of Subspace Clusters
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Elke Achtert,
Christian Böhm,
Hans-Peter Kriegel,
Peer Kröger,
Ina Müller-Gorman,
Arthur Zimek
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Integrating Pattern Mining in Relational Databases
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Toon Calders,
Bart Goethals,
Adriana Prado
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Discovering Patterns In Real-valued Time Series
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Joe Catalano,
Tom Armstrong,
Tim Oates
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Classification of Dementia Types from Cognitive Profiles Data
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Giorgio Corani,
Chris Edgar,
Isabelle Marshall,
Keith Wesnes,
Marco Zaffalon
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When Efficient Model Averaging Out-Performs Boosting and Bagging
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Ian Davidson,
Wei Fan
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Peak-Jumping Frequent Item Set Mining Algorithms
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Nele Dexters,
Paul W. Purdom,
Dirk Van Gucht
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Autonomous Visualization
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Khalid El-Arini,
Andrew Moore,
Ting Liu
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Naive Bayes for Text Classification with Unbalanced Classes
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Eibe Frank,
Remco Bouckaert
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Knowledge-Conscious Exploratory Data Clustering
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Amol Ghoting,
Srinivasan Parthasarathy
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On the Lower Bound of Reconstruction Error for Spectral Filtering Based Privacy Preserving Data Mining
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Songtao Guo,
Xintao Wu,
Yingjiu Li
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Frequent Pattern Discovery without Binarization: Mining Attribute Profiles
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Attila Gyenesei,
Ralph Schlapbach,
Etzard Stolte,
Ulrich Wagner
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Efficient Name Disambiguation for Large-Scale Databases
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Jian Huang,
Seyda Ertekin,
C. Lee Giles
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Adaptive Segmentation-Based Symbolic Representations of Time Series for Better Modeling and Lower Bounding Distance Measures
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Bernard Hugueney
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Feature Generation for Sequences: An Application to Splice Site Prediction
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Rezarta Islamaj,
Lise Getoor,
W. John Wilbur
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Discovering Image-Text Associations for Cross-Media Web Information Fusion
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Tao Jiang,
Ah-Hwee Tan
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Mining Sequences of Temporal Intervals
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Steffen Kempe,
Jochen Hipp
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Pattern Teams
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Arno Knobbe,
Eric Ho
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Compression picks Item Sets that Matter
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Matthijs van Leeuwen,
Jilles Vreeken,
Arno Siebes
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Discovering Overlapping Communities of Named Entities
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Xin Li,
Bing Liu,
Philip Yu
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Closed Non-Derivable Itemsets
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Juho Muhonen,
Hannu Toivonen
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Learning a Distance Metric for Object Identification without Human Supervision
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Satoshi Oyama,
Katsumi Tanaka
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Towards Association Rules with Hidden Variables
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Ricardo Silva,
Richard Scheines
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A Data Mining Approach to the Joint Evaluation of Field and Manufacturing Data in Automotive Industry
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Christian Manuel Strobel,
Tomas Hrycej
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Incremental Aspect Models for Mining Document Streams
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Arun Surendran,
Suvrit Sra
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Learning Approximate MRFs from Large Transaction Data
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Chao Wang,
Srinivasan Parthasarathy
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Similarity Search for Multi-dimensional NMR-Spectra of Natural Products
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Karina Wolfram,
Andrea Porzel,
Alexander Hinneburg
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