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Technical Committee on Infomation-Based Induction Sciences and Machine Learning (IBISML) [schedule] [select]
Chair Kenji Yamanishi (Univ. of Tokyo)
Vice Chair Naonori Ueda (NTT), Tomoyuki Higuchi (ISM)
Secretary Masashi Sugiyama (Tokyo Inst. of Tech.), Tsuyoshi Ide (IBM)
Assistant Daichi Mochihashi (ISM), Shigeyuki Ohba (Kyoto Univ.)

Conference Date Mon, Mar 12, 2012 10:00 - 17:45
Tue, Mar 13, 2012 10:00 - 17:45
Topics Mathematical Statistics, Databases, etc. 
Conference Place The Institute of Statistical Mathematics, Auditorium 
Address 10-3 Midori-cho, Tachikawa, Tokyo, Japan
Transportation Guide 10 minutes' walk from "Takamatsu" station of Tama monorail.
http://www.ism.ac.jp/access/index_e.html
Contact
Person
+81-50-5533-8500

Mon, Mar 12 AM  Bayesian Models
Chair: Daichi Mochihashi (ISM)
10:00 - 12:15
(1) 10:00-10:25 Chance Adjusted Infinite Relational Model for Asymmetric and Individually Different Relational Data Analysis Iku Ohama, Hiromi Iida (Panasonic), Takuya Kida, Hiroki Arimura (Hokkaido Univ.)
(2) 10:25-10:50 Bayesian Network Structure Estimation based on the Bayesian/MDL Criteria when both Discrete and Continuous Variables are Present Joe Suzuki (Osaka Univ.)
(3) 10:50-11:15 Detecting Latent Structural Changes via Latent Dirichlet Allocation Masashi Ueda, Ryota Tomioka, Kenji Yamanishi (The Univ. of Tokyo), Katsuhiko Ishiguro, Hiroshi Sawada, Naonori Ueda (NTT)
  11:15-11:25 Break ( 10 min. )
(4) 11:25-11:50 Fully Bayesian speaker clustering based on hierarchical structured Dirichlet process mixture model Naohiro Tawara, Tetsuji Ogawa (Waseda Univ.), Shinji Watanabe (NTT/MERL), Atsushi Nakamura (NTT), Tetsunori Kobayashi (Waseda Univ.)
(5) 11:50-12:15 Hyperparameter Selection of Infinite Gaussian Mixture Model via Widely Applicable Information Criterion Takushi Miki, Masahiro Kohjima, Sumio Watanabe (titech)
Mon, Mar 12 PM  Invited Talk (Data mining)
Chair: Tsuyoshi Ide (IBM Japan)
13:30 - 14:30
(6) 13:30-14:30 [Invited Talk]
Subsequence data mining revisited
Shin Ando (Gunma Univ.)
  14:30-14:40 Break ( 10 min. )
Mon, Mar 12 PM  Reinforcement Learning
Chair: Masashi Sugiyama (Tokyo Institute of Technology)
14:40 - 16:20
(7) 14:40-15:05 Kernel Bellman Equations in POMDPs Yu Nishiyama (ISM), Abdeslam Boularias (MPI), Arthur Gretton (UCL), Kenji Fukumizu (ISM)
(8) 15:05-15:30 Model Selection of Indirect Value Function Estimation Masahiro Kohjima (Tokyo Tech)
(9) 15:30-15:55 Apprenticeship Learning for Model Parameters of Partially Observable Environments Takaki Makino (Univ. of Tokyo), Johane Takeuchi (HRI-JP)
(10) 15:55-16:20 Efficient Sample Reuse in Policy Gradients with Parameter-based Exploration Tingting Zhao, Hirotaka Hachiya, Masashi Sugiyama (Tokyo Inst. of Tech.)
  16:20-16:30 Break ( 10 min. )
Mon, Mar 12 PM  Time series analysis
Chair: Shigeyuki Oba (Kyoto University)
16:30 - 17:45
(11) 16:30-16:55 Canonical Multiple Sequence Alignment for High-dimensional Multiple Time-series Analysis Takamitsu Matsubara (NAIST/ATR), Jun Morimoto (ATR)
(12) 16:55-17:20 Heterogeneous Time Series Clustering based on Infinite-Length Model Distance Shunsuke Hirose, Katsuyuki Izumi (SAS)
(13) 17:20-17:45 Detecting Long-term Trending Topics in Social Networks Shota Saito, Ryota Tomioka, Kenji Yamanishi (The Univ. of Tokyo)
Tue, Mar 13 AM  Statistical Mathematics
Chair: Kei Kobayashi (ISM)
10:00 - 10:50
(14) 10:00-10:25 On d-consistency for high-dimensional discrimination analysis Takanori Ayano (Osaka Univ.)
(15) 10:25-10:50 An Accuracy Analysis of Bayes Latent Variable Estimation with Redundant Variables Keisuke Yamazaki (Tokyo Inst. of Tech.)
  10:50-11:00 Break ( 10 min. )
Tue, Mar 13 AM  Learning Methods
Chair: Kei Kobayashi (ISM)
11:00 - 11:50
(16) 11:00-11:25 A Study on Decision Boundary Stability in Active Learning with Support Vector Machine Takeru Takahashi, Yuji Waizumi, Kazuo Hashimoto (Tohoku Univ.)
(17) 11:25-11:50 Semi-Supervised Learning of Class Balance under Class-Prior Change by Distribution Matching Marthinus Christoffel du Plessis, Masashi Sugiyama (Tokyo Inst. of Tech.)
Tue, Mar 13 PM  Invited Talk (Statistical Mathematics)
Chair: Daichi Mochihashi (ISM)
13:30 - 14:30
(18) 13:30-14:30 [Invited Talk]
Asymptotic estimation theory and Information geometry via computational algebra
Kei Kobayashi (ISM)
  14:30-14:40 Break ( 10 min. )
Tue, Mar 13 PM  Matrix factorization and applications
Chair: Toshihiro Kamishima (AIST)
14:40 - 15:30
(19) 14:40-15:05 Matrix and Tensor Factorization with Aggregated Observations Yoshifumi Aimoto, Hisashi Kashima (Univ. of Tokyo)
(20) 15:05-15:30 A Method for Packet Loss Rate Estimation Using Active and Passive Measurements Atsushi Miyamoto, Kazuho Watanabe, Kazushi Ikeda (NAIST)
  15:30-15:40 Break ( 10 min. )
Tue, Mar 13 PM  Active learning, Mutual information, ane else
Chair: Daichi Mochihashi (ISM)
15:40 - 17:45
(21) 15:40-16:05 Improving Importance Estimation in Pool-based Batch Active Learning for Approximate Linear Regression Nozomi Kurihara, Masashi Sugiyama (Tokyo Inst. of Tech.)
(22) 16:05-16:30 Early Stopping Heuristics in Pool-Based Incremental Active Learning for Least-Squares Probabilistic Classifier Tsubasa Kobayashi, Masashi Sugiyama (Tokyo Inst. of Tech.)
(23) 16:30-16:55 Feature Selection via L1-Penalized Squared-Loss Mutual Information Wittawat Jitkrittum, Hirotaka Hachiya, Masashi Sugiyama (Tokyo Inst. of Tech.)
(24) 16:55-17:20 Squared-loss Mutual Information Regularization Gang Niu, Wittawat Jitkrittum, Hirotaka Hachiya (Tokyo Inst. of Tech.), Bo Dai (Purdue Univ.), Masashi Sugiyama (Tokyo Inst. of Tech.)
(25) 17:20-17:45 The Information-Based Inductive Sciences and Biological Learning
-- The Quantum Mechanism of Concept (Digital Linguistics) --
Kimiaki Tokumaru (System Engineer)

Announcement for Speakers
General TalkEach speech will have 20 minutes for presentation and 5 minutes for discussion.

Contact Address and Latest Schedule Information
IBISML Technical Committee on Infomation-Based Induction Sciences and Machine Learning (IBISML)   [Latest Schedule]
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Last modified: 2012-03-13 09:40:43


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