Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010. Proceedings, Part I / Edition 1

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Overview

This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2010, held in Barcelona, Spain, in September 2010. The 120 revised full papers presented in three volumes, together with 12 demos (out of 24 submitted demos), were carefully reviewed and selected from 658 paper submissions. In addition, 7 ML and 7 DM papers were distinguished by the program chairs on the basis of their exceptional scientific quality and high impact on the field. The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. A topic widely explored from both ML and DM perspectives was graphs, with motivations ranging from molecular chemistry to social networks.

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Table of Contents

Invited Talks (Abstracts)

Mining Billion-Node Graphs: Patterns, Generators and Tools Christos Faloutsos 1

Structure Is Informative: On Mining Structured Information Networks Jiawei Han 2

Intelligent Interaction with the Real World Leslie Pack Kaelbling 3

Mining Experimental Data for Dynamical Invariants - From Cognitive Robotics to Computational Biology Hod Lipson 4

Hierarchical Learning Machines and Neuroscience of Visual Cortex Tomaso Poggio 5

Formal Theory of Fun and Creativity Jürgen Schmidhuber 6

Regular Papers

Porting Decision Tree Algorithms to Multicore Using FastFlow Marco Aldinucci Salvatore Ruggieri Massimo Torquati 7

On Classifying Drifting Concepts in P2P Networks Hock Hee Ang Vivekanand Gopalkrishnan Wee Keong Ng Steven Hoi 24

A Unified Approach to Active Dual Supervision for Labeling Features and Examples Josh Attenberg Prem Melville Foster Provost 40

Vector Field Learning via Spectral Filtering Luca Baldassarre Lorenzo Rosasco Annalisa Barla Alessandro Verri 56

Weighted Symbols-Based Edit Distance for String-Structured Image Classification Cécile Barat Christophe Ducottet Elisa Fromont Anne-Claire Legrand Marc Sebban 72

A Concise Representation of Association Rules Using Minimal Predictive Rules Iyad Batal Milos Hauskrecht 87

Euclidean Distances, Soft and Spectral Clustering on Weighted Graphs François Bavaud 103

Adaptive Parallel/Serial Sampling Mechanisms for Particle Filtering in Dynamic Bayesian Networks Eva Besada-Portas Sergey M. Plis Jesus M. de la Cruz Terran Lane 119

Leveraging Bagging for Evolving Data Streams Albert Bifet Geoff Holmes Bernhard Pfahringer 135

ITCH: Information-Theoretic Cluster Hierarchies Christian Böha Frank Fiedler Annahita Oswald Claudia Plant Bianca Wackersreuther Peter Wackersreuther 151

Coniunge et Impera: Multiple-Graph Mining for Query-Log Analysis Ilaria Bordino Debora Donato Ricardo Baeza- Yates 168

Process Mining Meets Abstract Interpretation J. Carmona J. Cortadella 184

Smarter Sampling in Model-Based Bayesian Reinforcement Learning Pablo Samuel Castro Doina Precup 200

Predicting Partial Orders: Ranking with Abstention Weiwei Cheng Michaël Rademaker Bernard De Baets Eyke Hüllermeier 215

Predictive Distribution Matching SVM for Multi-domain Learning Chun-Wei Seah Ivor W. Tsang Yew-Soon Ong Kee-Khoon Lee 231

Kantorovich Distances between Rankings with Applications to Rank Aggregation Stéphan Clémençon Jérémie Jakubowicz 248

Characteristic Kernels on Structured Domains Excel in Robotics and Human Action Recognition Somayeh Danafar Arthur Gretton Jürgen Schmidhuber 264

Regret Analysis for Performance Metrics in Multi-Label Classification: The Case of Hamming and Subset Zero-One Loss Krzysztof Dembczynski Willem Waegeman Weiwei Cheng Eyke Hüllermeier 280

Clustering Vessel Trajectories with Alignment Kernels under Trajectory Compression Gerben de Vries Maarten van Someren 296

Adaptive Bases for Reinforcement Learning Dotan Di Castro Shie Mannor 312

Constructing Nonlinear Discriminants from Multiple Data Views Tom Diethe David Roi Hardoon John Shawe-Taylor 328

Learning Algorithms for Link Prediction Based on Chance Constraints Janardhan Rao Doppa Jun Yu Prasad Tadepalli Lise Getoor 344

Sparse Unsupervised Dimensionality Reduction Algorithms Wenjun Dou Guang Dai Congfu Xu Zhihua Zhang 361

Asking Generalized Queries to Ambiguous Oracle Jun Du Charles X. Ling 377

Analysis of Large Multi-modal Social Networks: Patterns and a Generator Nan Du Hao Wang Christos Faloutsos 393

A Cluster-Level Semi-supervision Model for Interactive Clustering Avinava Dubey Indrajit Bhattacharya Shantanu Godbole 409

Software-Defect Localisation by Mining Dataflow-Enabled Call Graphs Frank Eichinger Klaus Krogmann Roland Klug Klemens Böhm 425

Induction of Concepts in Web Ontologies through Terminological Decision Trees Nicola Fanizzi Claudia d'Amato Floriana Esposito 442

Classification with Sums of Separable Functions Jochen Garcke 458

Feature Selection for Reinforcement Learning: Evaluating Implicit State-Reward Dependency via Conditional Mutual Information Hirotaka Hachiya Masashi Sugiyama 474

Bagging for Biclustering: Application to Microarray Data Blaise Hanczar Mohamed Nadif 490

Hub Gene Selection Methods for the Reconstruction of Transcription Networks José Miguel Hernández-Lobato Tjeerd M.H. Dijkstra 506

Expectation Propagation for Bayesian Multi-task Feature Selection Daniel Hernández-Lobato José Miguel Hernández-Lobato Thibault Helleputte Pierre Dupont 522

Graphical Multi-way Models Ilkka Huopaniemi Tommi Suvitaival Matej Orešic Samuel Kaski 538

Exploration-Exploitation of Eye Movement Enriched Multiple Feature Spaces for Content-Based Image Retrieval Zakria Hussain Alex P. Leung Kitsuchart Pasupa David R. Hardoon Peter Auer John Shawe- Taylor 554

Graph Regularized Transductive Classification on Heterogeneous Information Networks Ming Ji Yizhou Sun Marina Danilevsky Jiawei Han Jing Gao 570

Temporal Maximum Margin Markov Network Xiaoqian Jiang Bing Dong Latanya Sweeney 587

Gaussian Processes for Sample Efficient Reinforcement Learning with RMAX-Like Exploration Tobias Jung Peter Stone 601

Author Index 617

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