ACML2010  

Program

Program booklet (pdf)

Nov. 8 (Day 1)

08:30-10:00 Tutorial 1: Web People Search: Person Name Disambiguation and Other Problems, Minoru Yoshida and Hiroshi Nakagawa, (Chaired by Masashi Sugiyama)
10:00-10:20 Coffee Break
10:20-11:20 Tutorial 1: Web People Search: Person Name Disambiguation and Other Problems, Minoru Yoshida and Hiroshi Nakagawa, (Chaired by Masashi Sugiyama)
11:20-11:30 Break
11:30-12:30 Tutorial 2: Honest Evaluation of Classification Models, Jose A. Lozano, Guzman Santafe, and Inaki Inza (Chaired by Thomas G. Dietterich)
12:30-14:00 Lunch Break (on Your Own)
14:00-15:30 Tutorial 2: Honest Evaluation of Classification Models, Jose A. Lozano, Guzman Santafe, and Inaki Inza (Chaired by Thomas G. Dietterich)
15:30-15:50 Coffee Break
15:50-16:50 Tutorial 3: Support Vector Machines and Kernel Methods: Status and Challenges Chih-Jen Lin (Chaired by Koji Tsuda)
16:50-17:00 Break
17:00-18:00 Tutorial 3: Support Vector Machines and Kernel Methods: Status and Challenges, Chih-Jen Lin (Chaired by Koji Tsuda)



Nov. 9 (Day 2)

08:45-09:00 Opening
09:00-10:00 Invited Talk 1: Optimal Online Prediction in Adversarial Environments, Peter L. Bartlett (Chaired by Qiang Yang)
10:00-10:20 Coffee Break
10:20-11:40 Session 1: Statistical Learning (Chaired by Zhi-Hua Zhou)

Pairwise Measures of Causal Direction in Linear Non-Gaussian Acyclic Models
Aapo Hyvarinen, University of Helsinki

Learning Polyhedral Classifiers Using Logistic Function
Naresh Manwani, Indian Institute of Science; P. S. Sastry, Indian Institute of Science

Ellipsoidal Support Vector Machines
Michinari Momma, NEC; Kohei Hatano, Kyushu University; Hiroki Nakayama, NEC

Minimum Conditional Entropy Clustering: A Discriminative Framework for Clustering
Bo Dai, NLPR/LIAMA; Baogang Hu, NLPR/LIAMA

11:40-13:30 Lunch Break (on Your Own)
13:30-14:50 Session 2: Bayesian Learning (Chaired by Seungjin Choi)

Efficient Collapsed Gibbs Sampling for Latent Dirichlet Allocation
Han Xiao, Technical University of Munich; Thomas Stibor, Technical University of Munich

Variational Relevance Vector Machine for Tabular Data
Dmitry Kropotov, Dorodnicyn Computing Centre; Dmitry Vetrov, Lomonosov Moscow State University; Lior Wolf, Tel Aviv University; Tal Hassner, The Open University of Israel

Hierarchical Gaussian Process Regression
Sunho Park, POSTECH; Seungjin Choi, POSTECH

Content-based Image Retrieval with Multinomial Relevance Feedback
Dorota Glowacka, University College London; John Shawe-Taylor, University College London

14:50-15:00 Break
15:00-16:00 Invited Talk 2: Learning without Search, Geoff Webb (Chaired by Takashi Washio)
16:00-16:20 Coffee Break
16:20-18:00 Session 3: Discretization, Logic, Graphs, and Rules (Chaired by Yuji Matsumoto)

The Coding Divergence for Measuring the Complexity of Separating Two Sets
Mahito Sugiyama, Kyoto University; Akihiro Yamamoto, Kyoto University

Single versus Multiple Sorting in All Pairs Similarity Search
Yasuo Tabei, JST Minato ERATO Project; Takeaki Uno, National Institute of Informatics of Japan; Masashi Sugiyama, Tokyo Institute of Technology; Koji Tsuda, National Institute of Advanced Industrial Science and Technology

An EM Algorithm on BDDs with Order Encoding for Logic-based Probabilistic Models
Masakazu Ishihata, Tokyo Institute of Technology; Yoshitaka Kameya, Tokyo Institute of Technology; Taisuke Sato, Tokyo Institute of Technology; Shin-ichi Minato, Hokkaido University

Exploiting the High Predictive Power of Multi-class Subgroups
Tarek Abudawood, University of Bristol; Peter Flach, University of Bristol

Generative Models of Information Diffusion with Asynchronous Time-delay
Kazumi Saito, University of Shizuoka; Masahiro Kimura, Ryukoku University; Kouzou Ohara, Aoyama Gakuin University; Hiroshi Motoda, Osaka University

18:30-20:30 Banquet



Nov. 10 (Day 3)

09:00-10:00 Invited Talk 3: Kernel Method for Bayesian Inference, Kenji Fukumizu (Chaired by Masashi Sugiyama)
10:00-10:20 Coffee Break
10:20-11:40 Session 4: Stream and Large-scale Data (Chaired by Chih-Jen Lin)

Accurate Ensembles for Data Streams: Combining Restricted Hoeffding Trees using Stacking
Albert Bifet, University of Waikato; Eibe Frank, University of Waikato; Geoff Holmes, University of Waikato; Bernhard Pfahringer, University of Waikato

Mining Recurring Concept Drifts with Limited Labeled Streaming Data
Peipei Li, Hefei University of Technology; Xindong Wu, University of Vermont; Xuegang Hu, Hefei University of Technology

Hierarchical Convex NMF for Clustering Massive Data
Kristian Kersting, Fraunhofer IAIS and University of Bonn; Mirwaes Wahabzada, Fraunhofer IAIS; Christian Thurau, Fraunhofer IAIS; Christian Bauckhage, Fraunhofer IAIS

Multi-task Learning for Recommender System
Xia Ning, University of Minnesota; George Karypis, University of Minnesota

11:40-13:30 Lunch Break (on Your Own)
13:30-14:50 Session 5: Reinforcement Learning (Chaired by Remi Munos)

Adaptive Step-size Policy Gradients with Average Reward Metric
Takamitsu Matsubara, NAIST/ATR; Tetsuro Morimura, IBM Research; Jun Morimoto, ATR

Finite-sample Analysis of Bellman Residual Minimization
Odalric-Ambrym Maillard, INRIA; Alessandro Lazaric, INRIA Lille Nord-Europe; Remi Munos, INRIA Lille Nord-Europe

A Study of Approximate Inference in Probabilistic Relational Models
Fabian Kaelin, McGill; Doina Precup, McGill

Conceptual Imitation Learning: An Application to Human-robot Interaction
Hossein Hajimirsadeghi, University of Tehran; Majid Nili Ahmadabadi, University of Tehran; Mostafa Ajallooeian, University of Tehran; Babak Araabi, University of Tehran; Hadi Moradi, University of Tehran

14:50-15:00 Break
15:00-15:40 Poster Spotlight Session (Chaired by Masashi Sugiyama)
15:40-16:00 Coffee Break
16:00-18:00 Poster Session
18:00-18:10 Closing