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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
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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
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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
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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
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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
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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 |
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