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Technical Committee on Infomation-Based Induction Sciences and Machine Learning (IBISML)
Chair: Kenji Fukumizu (ISM)
Vice Chair: Masashi Sugiyama (Univ. of Tokyo), Hisashi Kashima (Kyoto Univ.)
Secretary: Koji Tsuda (Univ. of Tokyo), Ichiro Takeuchi (Nagoya Inst. of Tech.)
Assistant: Toshihiro Kamishima (AIST), Tomoharu Iwata (NTT)
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DATE:
Mon, Mar 6, 2017 13:30 - 17:30
Tue, Mar 7, 2017 10:00 - 14:30
PLACE:
Tokyo Institute of Technology, Ookayama campus(http://www.titech.ac.jp/english/maps/. Taiji Suzuki)
TOPICS:
Statistical Mathematics, Machine Learning, Data Mining, etc.
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Mon, Mar 6 PM Theory of machine learning (13:30 - 16:15)
Chair: Taiji Suzuki
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(1) 13:30 - 14:00
Tighter generalization bounds for matrix completion based on non-negative matrix factorization with norm constraints
Ken-ichiro Moridomi, Kohei Hatano, Eiji Takimoto (Kyushu Univ.)
(2) 14:00 - 14:30
Exact calculation of grid-structured Markov random field model by corner transfer matrix method
Tomoharu Yoshida, Kazuho Watanabe, Kyoji Umemura (Toyohashi Univ. of Tech.)
(3) 14:30 - 15:00
Degrees of freedom in submodular regularization
Kentaro Minami, Fumiyasu Komaki (The University of Tokyo)
----- Break ( 15 min. ) -----
(4) 15:15 - 16:15
Invited talk
Yuichi Yoshida (National Institute of Informatics)
"Constant time algorithms in machine learning"
----- Break ( 15 min. ) -----
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Mon, Mar 6 PM Deep learning (16:30 - 17:30)
Chair: Taiji Suzuki
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(5) 16:30 - 17:00
New Lerning Algorythm of Neural Network using Integral Representation and Kernel Herding
Takuo Matsubara, Sho Sonoda, Noboru Murata (Waseda Univ.)
(6) 17:00 - 17:30
Recurrent Neural Networks for task-evoked fMRI data classification
Koya Ohashi (Tokyo Tech), Taiji Suzuki (Tokyo Tech/JST/RIKEN)
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Tue, Mar 7 AM Optimization method (10:00 - 12:00)
Chair: Shunichi Nomura
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(7) 10:00 - 10:30
Safe Pruning Rule for Predictive Sequential Pattern Mining and Its Application to Bio-logging Data Analysis
Kaoru Kishimoto (NITech), Masayuki Karasuyama (NIT), Kazuya Nakagawa (NITech), Kotaro Kimura (Osaka Univ.), Ken Yoda (Nagoya Univ.), Yuta Umezu, Shinsuke Kajioka (NITech), Koji Tsuda (UTokyo), Ichiro Takeuchi (NITech)
(8) 10:30 - 11:00
Doubly Accelerated Stochastic Variance Reduced Gradient Method for Regularized Empirical Risk Minimization
Tomoya Murata, Taiji Suzuki (Tokyo Tech)
(9) 11:00 - 11:30
A study on minimizing size of sparse model optimization problem: exploiting safe rules for keeping and removing variables
Masayuki Karasuyama (NIT/NIMS/JST), Atsushi Shibagaki (NIT), Ichiro Takeuchi (NIT/NIMS/RIKEN/NIMS)
(10) 11:30 - 12:00
A stochastic optimization method and generalization bounds for voting classifiers by continuous density functions
Atsushi Nitanda (Tokyo Tech./NTTDATA MSI), Taiji Suzuki (Tokyo Tech./JST/RIKEN)
----- Lunch break ( 60 min. ) -----
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Tue, Mar 7 PM Applications of machine learning (13:00 - 14:30)
Chair: Taiji Suzuki
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(11) 13:00 - 13:30
Classification of In-week and -day Patterns of Ambulatory Activity Using a Hierarchical Topic Model and Interpolation of Step Counts in Missing Days
Shunichi Nomura (Tokyo Tech.), Michiko Watanabe, Yuko Oguma (Keio Univ.)
(12) 13:30 - 14:00
Topic model for analysis of gene expression data
Koji Iwayama (Ryukoku Univ.), Atsushi J. Nagano (Ryukoku Univ./Kyoto Univ.)
(13) 14:00 - 14:30
CTC network with explicit representation vector of Markov property
Yuta Kawachi, Taichi Asami, Yoshikazu Yamaguchi, Yushi Aono (NTT)
# Information for speakers
General Talk will have 25 minutes for presentation and 5 minutes for discussion.
=== Technical Committee on Infomation-Based Induction Sciences and Machine Learning (IBISML) ===
# FUTURE SCHEDULE:
Fri, Jun 23, 2017 - Sun, Jun 25, 2017: Okinawa Institute of Science and Technology [Tue, May 9], Topics: Machine Learning Approach to Biodata Mining, and General
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Last modified: 2017-01-24 17:54:16
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