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Technical Committee on Infomation-Based Induction Sciences and Machine Learning (IBISML)
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 (NTT), Shigeyuki Ohba (Kyoto Univ.)

DATE:
Wed, Nov 9, 2011 13:00 - 18:45
Thu, Nov 10, 2011 09:00 - 18:45
Fri, Nov 11, 2011 09:00 - 16:45

PLACE:


TOPICS:
The 14th IBIS workshop

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Wed, Nov 9 PM (13:00 - 15:30)
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Wed, Nov 9 PM (15:45 - 18:45)
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(1) 15:45 - 18:45
Decoding an Unknown Channel with Correlated Signals
Jian-Qin Liu (NICT), Teruya Yamanishi (Fukui Univ. of Tech.), Haruhiko Nishimura (Univ. of Hyogo), Hiroaki Umehara (NICT)

(2) 15:45 - 18:45
Local Minima Structure of Variational Bayes Learning
Fumito Nakamura, Sumio Watanabe (Tokyo Tech)

(3) 15:45 - 18:45
Asymptotic Eigenvalue Distribution of Random Matrix with Non-identical Variance Components
Takashi Shinzato (Akita Pref. Univ.)

(4) 15:45 - 18:45
Learning a Graphical Structure with Clusters
Satoshi Hara, Takashi Washio (Osaka Univ.)

(5) 15:45 - 18:45
Relative Density-Ratio Estimation for Robust Distribution Comparison
Makoto Yamada (Tokyo Inst. of Tech.), Taiji Suzuki (Univ. of Tokyo), Takafumi Kanamori (Nagoya Univ.), Hirotaka Hachiya, Masashi Sugiyama (Tokyo Inst. of Tech.)

(6) 15:45 - 18:45
Adaptive Markov Chain Monte Carlo for Auxiliary Variable Method and Its Application to Exchange Monte Carlo Method
Takamitsu Araki, Takashi Takenouchi, Kazushi Ikeda (NAIST)

(7) 15:45 - 18:45
Approximate Reduction from AUC Maximization to 1-norm Soft Margin Optimization
Daiki Suehiro, Kohei Hatano, Eiji Takimoto (Kyushu Univ.)

(8) 15:45 - 18:45
Kernel and Feature Search in Kernel PCA
Alam Md. Ashad (SOKENDAI), Kenji Fukumizu (ISM)

(9) 15:45 - 18:45
An Extension of Probabilistic PCA for Correlated Samples
Kohei Hayashi (NAIST), Masanori Kawakita (Kyushu Univ), Kazushi Ikeda (NAIST)

(10) 15:45 - 18:45
Active Value Function Estimation Based On Transition Probability Estimation
Masahiro Kohjima (Tokyo Tech)

(11) 15:45 - 18:45
Inferring the time-varying input signals and the hidden states from the membrane potential of a neuron
Ryota Kobayashi (Ritsumeikan Univ.), Petr Lansky (Acad. of Sci. of the Czech), Shigeru Shinomoto (Kyoto Univ.)

(12) 15:45 - 18:45
A kernel-based approach for matrix and tensor completion
Kohei Hayashi, Takashi Takenouchi (NAIST), Ryota Tomioka, Hisashi Kashima (Univ. Tokyo)

(13) 15:45 - 18:45
Modified Newton Approach to Policy Search
Hirotaka Hachiya (Tokyo Inst. of Tech.), Tetsuro Morimura (IBM Japan), Takaki Makino (Univ. of Tokyo), Masashi Sugiyama (Tokyo Inst. of Tech.)

(14) 15:45 - 18:45
An Accuracy Analysis of Latent Variable Estimation with the Maximum Likelihood Estimator
Keisuke Yamazaki (Tokyo Inst. of Tech.)

(15) 15:45 - 18:45
Prismatic algorithm for discrete D.C. programming problem
Yoshinobu Kawahara, Takashi Washio (Osaka Univ.)

(16) 15:45 - 18:45
Multiple Kernel Learning Based on Gaussianity
Hideitsu Hino, Noboru Murata (Waseda Univ.)

(17) 15:45 - 18:45
Gaussian FoE model with correlations among color components
Ryuta Murayama, Muneki Yasuda, Yuji Waizumi, Kazuyuki Tanaka (Tohoku Univ.)

(18) 15:45 - 18:45
Extraction of Damage Patterns of a Fuel Cell by Clustering Considering Co-occurrence between Events
Daiki Inaba, Ken-ichi Fukui (Osaka Univ.), Kazuhisa Sato, Junichirou Mizusaki (Tohoku Univ.), Masayuki Numao (Osaka Univ.)

(19) 15:45 - 18:45
Replica Symmetry Breaking in Compressed Sensing
Koujin Takeda, Yoshiyuki Kabashima (Tokyo Tech.)

(20) 15:45 - 18:45
Generalization of Matrix Factorization for Robust PCA
Shinichi Nakajima (Nikon), Masashi Sugiyama (Tokyo Inst. of Tech.), Derin Babacan (Illinois Univ.)

(21) 15:45 - 18:45
Detecting Changes of Clustering Structures using Renormalized Maximum Likelihood Coding
So Hirai, Kenji Yamanishi (Univ. of Tokyo)

(22) 15:45 - 18:45
POS prediction using collaborative filtering
Tor Andre Myrvoll (SINTEF), Tomoko Matsui (ISM)

(23) 15:45 - 18:45
On Fast Convergence Rate of Non-Sparse Multiple Kernel Learning and Optimal Regularization
Taiji Suzuki (Tokyo University)

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Thu, Nov 10 PM (09:00 - 11:00)
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Thu, Nov 10 PM (11:00 - 12:30)
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----- Lunch Break ( 60 min. ) -----

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Thu, Nov 10 PM (13:30 - 15:30)
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Thu, Nov 10 PM (15:45 - 18:45)
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(24) 15:45 - 18:45
A Method for Estimating Binary Data Generating Process
Takanori Inazumi, Takashi Washio, Shohei Shimizu, Joe Suzuki (Osaka Univ.), Akihiro Yamamoto (Kyoto Univ.), Yoshinobu Kawahara (Osaka Univ.)

(25) 15:45 - 18:45
Dynamic model selection with resetting distributions
Eiichi Sakurai (AIST), Kenji Yamanishi (The Univ. of Tokyo)

(26) 15:45 - 18:45
Image Segmentation and Restoration using Switching State-Space Model and Variational Bayesian Method
Ryota Hasegawa (Kansai Univ.), Ken Takiyama, Masato Okada (Univ. of Tokyo), Seiji Miyoshi (Kansai Univ.)

(27) 15:45 - 18:45
Image segmentation and restoration by variational Bayesian method and MCMC
Kenta Kayano (Kansai Univ.), Kenji Nagata, Masato Okada (Univ. of Tokyo), Seiji Miyoshi (Kansai Univ.)

(28) 15:45 - 18:45
Estimation of Recombination Rates by Using Dirichlet Process and Variational Bayes
Yuna Yomogida, Noboru Murata, Masato Inoue (Waseda Univ.)

(29) 15:45 - 18:45
Change-Point Detection in Time-Series Data by Relative Density-Ratio Estimation
Song Liu, Makoto Yamada, Masashi Sugiyama (Tokyo Inst. of Tech.)

(30) 15:45 - 18:45
Sequential Network Change Detection with Its Applications to Advertisement Impact Relation Analysis
Yu Hayashi, Kenji Yamanishi (Univ. of Tokyo.)

(31) 15:45 - 18:45
Causal Inference for Discrete Data
-- Extension from binary data to multi-value data. --
Joe Suzuki, Shohei Shimizu, Takashi Washio (Osaka U.)

(32) 15:45 - 18:45
Computationally Efficient Multi-Label Classification by Least-Squares Probabilistic Classifier
Hyunha Nam, Hirotaka Hachiya, Masashi Sugiyama (Tokyo Inst. of Tech.)

(33) 15:45 - 18:45
A latent variational approximation method of Total variation for noise reduction
Hayaru Shouno (UEC), Masato Okada (The Univ. of Tokyo)

(34) 15:45 - 18:45
Image Restoration and Segmentation Based on Compound Gaussian Markov Random Field Extended as Mixture Model
Takayuki Katsuki, Masato Inoue (Waseda Univ.)

(35) 15:45 - 18:45
A convex formulations of learning from crowds
Hiroshi Kajino, Hisashi Kashima (UT)

(36) 15:45 - 18:45
On the behavior of average of acceptance rate for Metropolis algorithm
Kenji Nagata (Univ. of Tokyo), Masato Okada (Univ. of Tokyo/RIKEN)

(37) 15:45 - 18:45
Nonparametric Estimation of Mixture Model and Minimum Divergence Methods
Kazuho Watanabe (NAIST), Shiro Ikeda (ISM)

(38) 15:45 - 18:45
Semi-supervised domain adaptation with multiple kernel learning
Hiroyuki Okada, Kuniaki Uehara (Kobe Univ.)

(39) 15:45 - 18:45
Effectiveness of Laplacian-based kernels from the hubness point of view
Ikumi Suzuki (NAIST), Kazuo Hara (NIG), Masashi Shimbo, Yuji Matsumoto (NAIST)

(40) 15:45 - 18:45
A Parametric Programming Approach for Outlier Detection and Robust Learning for Classification and Regression
Ichiro Takeuchi (NIT)

(41) 15:45 - 18:45
Generation of Language among Learning Machines
-- Modelling Natural Language Generation --
Seisuke Yanagawa (Optid)

(42) 15:45 - 18:45
Detection of miscategorized samples based on predictive likelihood maximization
Akinori Fujino, Tomoharu Iwata, Masaaki Nagata (NTT)

(43) 15:45 - 18:45
Mixture of Regression Based on Basis Functions Derived from Binomial Distribution
Gen Nakagata, Masato Inoue (Waseda Univ)

(44) 15:45 - 18:45
A Linear Time Subpath Kernel for Trees
Daisuke Kimura, Hisashi Kashima (Univ. of Tokyo)

(45) 15:45 - 18:45
Clustering and planning for 3D near-infrared sensor data by Hierarchical Dirichlet Process
Takayuki Shimotomai, Hiroyuki Okada, Takashi Omori (Tamagawa Univ.)

----- Banquet ( 120 min. ) -----

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Fri, Nov 11 AM (09:00 - 12:00)
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----- Lunch Break ( 60 min. ) -----

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Fri, Nov 11 PM (13:00 - 14:30)
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Fri, Nov 11 PM (14:45 - 16:45)
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=== Technical Committee on Infomation-Based Induction Sciences and Machine Learning (IBISML) ===


Last modified: 2011-09-22 17:47:06


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