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Full Schedule


Sunday 19 September

17:00 - 20:00 Pick-up of registration materials for pre-registrered participant, Casa de Convalescència

(note: no on-site registration is possible on Sunday)

Monday 20 September

8:00 - 19:00: Registration desk is open

9:00 - 17:30: Workshops and tutorials, including Discovery Challenge workshop

18:00 - 18:30: Opening and awards ceremony

18:30 - 19:30: Invited talk by Hod Lipson

19:30 - : Welcome reception

Tuesday 21 September

9:00 - 9:20: Announcements

9:20 - 10:20: Invited talk by Tomaso Poggio

Session 1: Rules and Patterns 1

Tuesday 21 September
10:50 - 12:40, aula magna

Chair: Jilles Vreeken

Mining Top-k Frequent Itemsets Through Progressive Sampling
Andrea Pietracaprina, Matteo Riondato, Eli Upfal, Fabio Vandin

Integrating Constraint Programming and Itemset Mining
Siegfried Nijssen, Tias Guns

Using Background Knowledge to Rank Itemsets

Nikolaj Tatti, Michael Mampaey

NDPMine: Efficiently Mining Discriminative Numerical Features for Pattern-Based Classification

Hyungsul Kim, Sangkyum Kim, Tim Weninger, Jiawei Han, Tarek Abdelzaher

Adverse Drug Reaction Mining in Pharmacovigilance data using Formal Concept Analysis
Jean Villerd, Yannick Toussaint, Agnès Lillo-Le Louët

Session 2: Bayesian Learning 1

Tuesday 21 September
10:50 - 12:40, room 11-13

Chair: Ulf Brefeld

Three Approaches for Making the Naive Bayes Classifier Discrimination-Free

Sicco Verwer, Toon Calders

Nonparametric Bayesian Clustering Ensembles
Pu Wang, Carlotta Domeniconi, Kathryn Blackmond Laskey

Large Margin Learning of Bayesian Classifiers based on Gaussian Mixture Models

Franz Pernkopf, Michael Wohlmayr

Variational Bayesian mixture of robust CCA models

Jaakko Viinikanoja, Arto Klami, Samuel Kaski

Graphical Multi-Way Models
Ilkka Huopaniemi, Tommi Suvitaival, Matej Oresic, Samuel Kaski

Session 3: Ensemble Learning

Tuesday 21 September
10:50 - 12:40, room 10-12

Chair: TBA

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

Learning with Ensemble of Randomized Trees: New Insights
Vincent Pisetta, Pierre-Emmanuel Jouve, Djamel A. Zighed

Learning with Randomized Majority Votes

Alexandre Lacasse, François Laviolette, Mario Marchand, Francis Turgeon-Boutin

Bagging for Biclustering: Application to Microarray Data

Blaise Hanczar, Mohamed Nadif

Recognition of Instrument Timbres in Real Polytimbral Audio Recordings
Elzbieta Kubera, Alicja Wieczorkowska, Zbigniew Ras, Magdalena Skrzypiec

Session 4: Web Mining and Collaborative Tagging

Tuesday 21 September
14:20 - 16:10, aula magna

Chair: Carlos Castillo

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

Demand-Driven Tag Recommendation

Guilherme Vale Menezes, Jussara Almeida, Fabiano Belém, Marcos André Gonçalves, Anísio Lacerda, Edleno Silva de Moura, Gisele L. Pappa, Adriano Veloso, Nivio Ziviani

Learning to Tag From Open Vocabulary Labels
Edith Law, Burr Settles, Tom Mitchell

Efficient Confident Search in Large Review Corpora
Theodoros Lappas, Dimitrios Gunopulos

Large Scale Image Annotation: Learning to Rank with Joint Word-Image Embeddings

Jason Weston, Samy Bengio, Nicolas Usunier

Session 5: Kernel Methods

Tuesday 21 September
14:20 - 16:10, room 11-13

Chair: Thore Graepel

A Unifying View of Multiple Kernel Learning
Marius Kloft, Ulrich Rückert, Peter L. Bartlett

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

Vector Field Learning via Spectral Filtering
Luca Baldassarre, Lorenzo Rosasco, Annalisa Barla, Alessando Verri

Many-to-Many Graph Matching: a Continuous Relaxation Approach
Mikhail Zaslavskiy, Francis Bach, Jean-Philippe Vert

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

Session 6: Topic Models and Dimensionality Reduction

Tuesday 21 September
14:20 - 16:10, room 10-12

Chair: Geoff Webb

A Segmented Topic Model Based on the Two-parameter Poisson-Dirichlet Process
Lan Du, Wray Buntine, Huidong Jin

Topic Models Conditioned on Relations

Mirwaes Wahabzada, Zhao Xu, Kristian Kersting

Topic Modeling for Personalized Recommendation of Volatile Items

Maks Ovsjanikov, Ye Chen

Learning an Affine Transformation for Non-linear Dimensionality Reduction
Pooyan Khajehpour Tadavani, Ali Ghodsi

Sparse Unsupervised Dimensionality Reduction Algorithms
Wenjuan Dou, Guang Dai, Congfu Xu, Zhihua Zhang

Session 7: Link Prediction and Graph Classification

Tuesday 21 September
16:40 - 18:30, aula magna

Chair: Bjorn Bringmann

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

Graph Regularized Transductive Classification on Heterogeneous Information Networks

Ming Ji, Yizhou Sun, Marina Danilevsky, Jiawei Han, Jing Gao

Fast and Scalable Algorithms for Semi-supervised Link Prediction on Static and Dynamic Graphs
Rudy Raymond, Hisashi Kashima

Directed Graph Learning via High-Order Co-linkage Analysis

Hua Wang, Chris Ding, Heng Huang

Predicting Labels for Dyadic Data
Aditya Menon, Charles Elkan

Session 8: Reinforcement Learning 1

Tuesday 21 September
16:40 - 18:30, room 11-13

Chair: Irina Rish


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

Incorporating Domain Models into Bayesian Optimization for Reinforcement Learning

Aaron Wilson, Alan Fern, Prasad Tadepalli

Gaussian Processes for Sample Efficient Reinforcement Learning with RMAX-Like Exploration

Tobias Jung, Peter Stone

Exploration in Relational Worlds

Tobias Lang, Marc Toussaint, Kristian Kersting

Evolutionary Dynamics of Regret Minimization

Tomas Klos, Gerrit Jan van Ahee, Karl Tuyls

Session 9: Multi-task, Multi-domain and Large-scale Learning

Tuesday 21 September
16:40 - 18:30, room 10-12

Chair: Katharina Morik

Shift-invariant Grouped Multi-task Learning for Gaussian Processes

Yuyang Wang, Roni Khardon, Pavlos Protopapas

Cross Validation Framework to Choose amongst Models and Datasets for Transfer Learning
Erheng Zhong, Wei Fan, Qiang Yang, Olivier Verscheure, Jiangtao Ren

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

Porting Decision Tree Algorithms to Multicore Using FastFlow

Marco Aldinucci, Salvatore Ruggieri, Massimo Torquati

Large Scale Support Vector Learning with Structural Kernels
Aliaksei Severyn, Alessandro Moschitti

19:20 - : Poster reception 1 at Institut d'Estudis Catalans

Wednesday 22 September

9:00 - 9:20: Announcements

9:20 - 10:20: Invited talk by Jiawei Han

Session 10: Social Networks

Wednesday 22 September
10:50 - 12:40, aula magna

Chair: Tanya Berger-Wolf

Selecting Information Diffusion Models over Social Networks for Behavioral Analysis
Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda

Finding Critical Nodes for Inhibiting Diffusion of Complex Contagions in Social Networks

Chris J. Kuhlman, V. S. Anil Kumar, Madhav V. Marathe, S. S. Ravi, Daniel J. Rosenkrantz

Analysis of Large Multi-Modal Social Networks: Patterns and a Generator

Nan Du, Hao Wang, Christos Faloutsos

Surprising Patterns for the Call Duration Distribution of Mobile Phone Users

Pedro O. S. Vaz de Melo, Leman Akoglu, Christos Faloutsos, Antonio A. F. Loureiro

Virus Propagation on Time-Varying Networks: Theory and Immunization Algorithms
B. Aditya Prakash, Hanghang Tong, Nicholas Valler, Michalis Faloutsos, Christos Faloutsos

Session 11: Bayesian Learning 2

Wednesday 22 September
10:50 - 12:40, room 11-13

Chair: Hendrik Blockeel

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

A Geometric View of Conjugate Priors
Arvind Agarwal, Hal Daume

Permutation Testing Improves Bayesian Network Learning
Ioannis Tsamardinos, Giorgos Borboudakis

An Efficient and Scalable Algorithm for Local Bayesian Network Structure Discovery
Sérgio Rodrigues De Morais, Alex Aussem

Bayesian Knowledge Corroboration with Logical Rules and User Feedback

Gjergji Kasneci, Jurgen Van Gael, Ralf Herbrich, Thore Graepel

Session 12: Sparse Learning

Wednesday 22 September
10:50 - 12:40, room 10-12

Chair: Roni Khardon

Classification with Sums of Separable Functions
Jochen Garcke

Solving Structured Sparsity Regularization with Proximal Methods
Sofia Mosci, Lorenzo Rosasco, Matteo Santoro, Alessando Verri, Silvia Villa

Learning Sparse Gaussian Markov Networks Using a Greedy Coordinate Ascent Approach

Katya Scheinberg, Irina Rish

Efficient and Numerically Stable Sparse Learning

Sihong Xie, Wei Fan, Olivier Verscheure, Jiangtao Ren

k-Version-Space Multi-Class Classification Based on k-Consistency Tests

Evgueni Smirnov, Georgi Nalbantov, Nikolay Nikolaev

Session 13: Active and Adversarial Learning

Wednesday 22 September
14:20 - 16:10, aula magna

Chair: Peter Flach

Asking Generalized Queries to Ambiguous Oracle

Jun Du, Charles X. Ling

Complexity Bounds for Batch Active Learning in Classification

Philippe Rolet, Olivier Teytaud

A Unified Approach to Active Dual Supervision for Labeling Features and Examples

Josh Attenberg, Prem Melville, Foster Provost

Mining Adversarial Patterns via Regularized Loss Minimization
Wei Liu, Sanjay Chawla

Online Learning in Adversarial Lipschitz Environments

Odalric-Ambrym Maillard, Rémi Munos

Session 14: Relational Learning

Wednesday 22 September
14:20 - 16:10, room 11-13

Chair: Dunja Mladenic

First-Order Bayes-Ball
Wannes Meert, Nima Taghipour, Hendrik Blockeel

Temporal Maximum Margin Markov Network

Xiaoqian Jiang, Bing Dong, Latanya Sweeney

Entropy and Margin Maximization for Structured Output Learning

Patrick Pletscher, Cheng Soon Ong, Joachim M. Buhmann

Modeling Relations and Their Mentions without Labeled Text
Sebastian Riedel, Limin Yao, Andrew McCallum

Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models
Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasad Tadepalli, Kristian Kersting, Jude Shavlik

Session 15: Graph Mining

Wednesday 22 September
14:20 - 16:10, room 10-12

Chair: Hiroshi Motoda

Online Structural Graph Clustering Using Frequent Subgraph Mining
Madeleine Seeland, Tobias Girschick, Fabian Buchwald, Stefan Kramer

Latent Structure Pattern Mining
Andreas Maunz, Christoph Helma, Tobias Cramer, Stefan Kramer

Relational Retrieval Using a Combination of Path-Constrained Random Walks
Ni Lao, William Cohen

Coniunge et Impera: Multiple-Graph Mining for Query-Log Analysis

Ilaria Bordino, Debora Donato, Ricardo Baeza-Yates

Hub Gene Selection Methods for the Reconstruction of Transcription Networks
José Miguel Hernández Lobato, Tjeerd Dijkstra

17:30 - 19:00: Guided visits of Palau de la Musica Catalana

19:00 - 20:00: Invited talk by Juergen Schmidhuber, Petit Palau

20:00 - : Gala dinner, Palau de la Musica Catalana

Thursday 23 September

9:00 - 9:20: Announcements

9:20 - 10:20: Invited talk by Leslie Pack Kaelbling

Session 16: Spectral Analysis and Graph Clustering

Thursday 23 September
10:50 - 12:40, aula magna

Chair: Stefan Wrobel

Euclidean Distances, Soft and spectral Clustering on Weighted Graphs
François Bavaud

Improved MinMax Cut Graph Clustering with Non-negative Relaxation

Feiping Nie, Chris Ding, Dijun Luo, Heng Huang

A Game-Theoretic Framework to Identify Overlapping Communities in Social Networks

Wei Chen, Zhenming Liu, Xiaorui Sun, Yajun Wang

Laplacian Spectrum Learning
Pannagadatta K. Shivaswamy, Tony Jebara

On The Eigenvectors of p-Laplacian

Dijun Luo, Chris Ding, Heng Huang, Feiping Nie

Session 17: Rankings and Partial Orders

Thursday 23 September
10:50 - 12:40, room 11-13

Chair: Johannes Furnkranz

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

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

Conditional Ranking on Relational Data

Tapio Pahikkala, Willem Waegeman, Antti Airola, Tapio Salakoski, Bernard De Baets

Fast Active Exploration for Link-Based Preference Learning Using Gaussian Processes

Zhao Xu, Kristian Kersting, Thorsten Joachims

Adapting Decision DAGs for Multipartite Ranking

José Ramón Quevedo, Elena Montañés, Oscar Luaces, Juan José del Coz

Session 18: Reinforcement Learning 2

Thursday 23 September
10:50 - 12:40, room 10-12

Chair: Leslie Kaelbling

Feature Selection for Reinforcement Learning: Evaluating Implicit State-Reward Dependency via Conditional Mutual Information

Hirotaka Hachiya, Masashi Sugiyama

Adaptive Bases for Reinforcement Learning
Dotan Di Castro, Shie Mannor

Dimension Reduction and Its Application to Model-based Exploration in Continuous Spaces
Ali Nouri, Michael Littman

Efficient Planning in Large POMDPs through Policy Graph Based Factorized Approximations
Joni Pajarinen, Jaakko Peltonen, Ari Hottinen, Mikko A. Uusitalo

Learning from Demonstration Using MDP Induced Metrics
Francisco S. Melo, Manuel Lopes

Session 19: Rules and Patterns 2

Thursday 23 September
14:20 - 16:10, aula magna

Chair: Toon Calders

A Concise Representation of Association Rules using Minimal Predictive Rules
Iyad Batal, Milos Hauskrecht

A Measure of Robustness of Association Rules

Yannick Le Bras, Patrick Meyer, Philippe Lenca, Stéphane Lallich

Fast Extraction of Locally Optimal Patterns Based on Consistent Pattern Function Variations

Frédéric Pennerath

Maximal Exceptions with Minimal Descriptions
Matthijs van Leeuwen

Fast, Effective Molecular Feature Mining by Local Optimization
Albrecht Zimmermann, Björn Bringmann, Ulrich Rückert

Session 20: Learning and Mining in Dynamic Domains

Thursday 23 September
14:20 - 16:10, room 11-13

Chair: TBA

Weighted Symbols-Based Edit Distance for String-Structured Image Classification

Cécile Barat, Christophe Ducottet, Elisa Fromont, Anne-Claire Legrand, Marc Sebban

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

Hidden Conditional Ordinal Random Fields for Sequence Classification

Minyoung Kim, Vladimir Pavlovic

Classification and Novel Class Detection of Data Streams in A Dynamic Feature Space

Mohammad M. Masud, Qing Chen, Jing Gao, Latifur Khan, Jiawei Han, Bhavani Thuraisingham

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

Session 21: Online Learning

Thursday 23 September
14:20 - 16:10, room 10-12

Chair: Einoshin Suzuki

Automatic Model Adaptation for Complex Structured Domains
Geoffrey Levine, Gerald DeJong, Li-Lun Wang, Rajhans Samdani, Shankar Vembu, Dan Roth

Competitive Online Generalized Linear Regression under Square Loss
Fedor Zhdanov, Vladimir Vovk

Online Knowledge-Based Support Vector Machines
Gautam Kunapuli, Kristin P. Bennett, Amina Shabbeer, Richard Maclin, Jude Shavlik

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

Example-dependent Basis Vector Selection for Kernel-Based Classifiers
Antti Ukkonen, Marta Arias

Session 22: Semi-supervised Learning

Thursday 23 September
16:40 - 18:30, aula magna

Chair: Charles Elkan

Accelerating Spectral Clustering with Partial Supervision
Dimitrios Mavroeidis

A Cluster-Level Semi-Supervision Model for Interactive Clustering
Avinava Dubey, Indrajit Bhattacharya, Shantanu Godbole

Semi-supervised Projection Clustering with Transferred Centroid Regularization

Bin Tong, Hao Shao, Bin-Hui Chou, Einoshin Suzuki

Constrained Parameter Estimation for Semi-Supervised Learning: The Case of the Nearest Mean Classifier
Marco Loog

Semi-Supervised Abstraction-Augmented String Kernel for Multi-Level Bio-Relation Extraction

Pavel Kuksa, Yanjun Qi, Bing Bai, Ronan Collobert, Jason Weston, Vladimir Pavlovic, Xia Ning

Session 23: Trajectory Mining and Process Mining

Thursday 23 September
16:40 - 18:30, room 11-13

Chair: Latifur Khan

Collective Traffic Forecasting
Marco Lippi, Matteo Bertini, Paolo Frasconi

Unsupervised Trajectory Sampling
Nikos Pelekis, Ioannis Kopanakis, Costas Panagiotakis, Yannis Theodoridis

Clustering Vessel Trajectories with Alignment Kernels under Trajectory Compression

Gerben De Vries, Maarten van Someren

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

Process Mining Meets Abstract Interpretation
Josep Carmona, Jordi Cortadella

Session 24: MDL, Outliers, and Anomalies

Thursday 23 September
16:40 - 18:30, room 10-12

Chair: Arno Siebes

Summarising Data by Clustering Items

Michael Mampaey, Jilles Vreeken

ITCH: Information-Theoretic Cluster Hierarchies

Christian Böhm, Frank Fiedler, Annahita Oswald, Claudia Plant, Bianca Wackersreuther, Peter Wackersreuther

Synchronization Based Outlier Detection

Junming Shao, Christian Böhm, Qinli Yang, Claudia Plant

On Detecting Clustered Anomalies using SCiForest

Fei Tony Liu, Kai Ming Ting, Zhi-Hua Zhou

Software-Defect Localisation by Mining Dataflow-Enabled Call Graphs

Frank Eichinger, Klaus Krogmann, Roland Klug, Klemens Bhöm

18:30 - 19:30: Community meeting, Casa de Convalescència

19:45 - : Poster reception 2 at Universitat de Barcelona

Friday 24 September

9:00 - 10:00: Invited talk by Christos Faloutsos

10:30 - 18:30: Workshops and tutorials, including Industrial Session

18:30 - : Farewell cava





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