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Technical Committee on Information-Based Induction Sciences and Machine Learning (IBISML)  (Searched in: 2011)

Search Results: Keywords 'from:2011-11-09 to:2011-11-09'
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Search Results: Conference Papers
 Conference Papers (Available on Advance Programs)  (Sort by: Date Ascending)
 Results 21 - 40 of 45 [Previous]  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
IBISML 2011-11-09
15:45		 Nara Nara Womens Univ. Detecting Changes of Clustering Structures using Renormalized Maximum Likelihood Coding
So Hirai, Kenji Yamanishi (Univ. of Tokyo) IBISML2011-62		 Suppose that we sequentially observe multi-dimensional data sets, which are non-stationary. We are concerned with the i... [more] IBISML2011-62
pp.135-142
IBISML 2011-11-09
15:45		 Nara Nara Womens Univ. POS prediction using collaborative filtering
Tor Andre Myrvoll (SINTEF), Tomoko Matsui (ISM) IBISML2011-63		  [more] IBISML2011-63
pp.143-146
IBISML 2011-11-09
15:45		 Nara Nara Womens Univ. On Fast Convergence Rate of Non-Sparse Multiple Kernel Learning and Optimal Regularization
Taiji Suzuki (Tokyo University) IBISML2011-64		 In this paper, we give a new generalization error bound of Multiple Kernel Learning (MKL) for a general class of regular... [more] IBISML2011-64
pp.147-154
IBISML 2011-11-10
15:45		 Nara Nara Womens Univ. 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.) IBISML2011-65		 In our previous study, we proposed a method to identify a data generation process governing its given binary data set. H... [more] IBISML2011-65
pp.155-162
IBISML 2011-11-10
15:45		 Nara Nara Womens Univ. Dynamic model selection with resetting distributions
Eiichi Sakurai (AIST), Kenji Yamanishi (The Univ. of Tokyo) IBISML2011-66		 We are concerned with the issue of tracking changes of statistical models (e.g. the number of parameters, a discrete mod... [more] IBISML2011-66
pp.163-168
IBISML 2011-11-10
15:45		 Nara Nara Womens Univ. 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.) IBISML2011-67		 We derive a deterministic algorithm that restores and segments image using switching state-space model and variational B... [more] IBISML2011-67
pp.169-174
IBISML 2011-11-10
15:45		 Nara Nara Womens Univ. 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.) IBISML2011-68		 In this paper, we derive a deterministic algorithm that restores and segments an image by using variational Bayesian met... [more] IBISML2011-68
pp.175-180
IBISML 2011-11-10
15:45		 Nara Nara Womens Univ. Estimation of Recombination Rates by Using Dirichlet Process and Variational Bayes
Yuna Yomogida, Noboru Murata, Masato Inoue (Waseda Univ.) IBISML2011-69		  [more] IBISML2011-69
pp.181-185
IBISML 2011-11-10
15:45		 Nara Nara Womens Univ. Change-Point Detection in Time-Series Data by Relative Density-Ratio Estimation
Song Liu, Makoto Yamada, Masashi Sugiyama (Tokyo Inst. of Tech.) IBISML2011-70		 The objective of change-point detection is to discover abrupt property changes lying behind time series data. In this pa... [more] IBISML2011-70
pp.187-198
IBISML 2011-11-10
15:45		 Nara Nara Womens Univ. Sequential Network Change Detection with Its Applications to Advertisement Impact Relation Analysis
Yu Hayashi, Kenji Yamanishi (Univ. of Tokyo.) IBISML2011-71		 This paper addresses the issue of network change detection from non-stationary time series data. We employ as a represen... [more] IBISML2011-71
pp.199-206
IBISML 2011-11-10
15:45		 Nara Nara Womens Univ. Causal Inference for Discrete Data -- Extension from binary data to multi-value data. --
Joe Suzuki, Shohei Shimizu, Takashi Washio (Osaka U.) IBISML2011-72		  [more] IBISML2011-72
pp.207-212
IBISML 2011-11-10
15:45		 Nara Nara Womens Univ. Computationally Efficient Multi-Label Classification by Least-Squares Probabilistic Classifier
Hyunha Nam, Hirotaka Hachiya, Masashi Sugiyama (Tokyo Inst. of Tech.) IBISML2011-73		  [more] IBISML2011-73
pp.213-216
IBISML 2011-11-10
15:45		 Nara Nara Womens Univ. A latent variational approximation method of Total variation for noise reduction
Hayaru Shouno (UEC), Masato Okada (The Univ. of Tokyo) IBISML2011-74		 (To be available after the conference date) [more] IBISML2011-74
pp.217-222
IBISML 2011-11-10
15:45		 Nara Nara Womens Univ. Image Restoration and Segmentation Based on Compound Gaussian Markov Random Field Extended as Mixture Model
Takayuki Katsuki, Masato Inoue (Waseda Univ.) IBISML2011-75		 This report proposes an accurate image restoration and segmentation using a new image model. The model is a compound Gau... [more] IBISML2011-75
pp.223-230
IBISML 2011-11-10
15:45		 Nara Nara Womens Univ. A convex formulations of learning from crowds
Hiroshi Kajino, Hisashi Kashima (UT) IBISML2011-76		 It has attracted considerable attention to use crowdsourcing services
to collect a large amount of labeled data for ma... [more]		 IBISML2011-76
pp.231-236
IBISML 2011-11-10
15:45		 Nara Nara Womens Univ. On the behavior of average of acceptance rate for Metropolis algorithm
Kenji Nagata (Univ. of Tokyo), Masato Okada (Univ. of Tokyo/RIKEN) IBISML2011-77		  [more] IBISML2011-77
pp.237-242
IBISML 2011-11-10
15:45		 Nara Nara Womens Univ. Nonparametric Estimation of Mixture Model and Minimum Divergence Methods
Kazuho Watanabe (NAIST), Shiro Ikeda (ISM) IBISML2011-78		 We discuss a nonparametric estimation method of the mixing distribution in mixture models.
We propose an objective fun... [more]		 IBISML2011-78
pp.243-249
IBISML 2011-11-10
15:45		 Nara Nara Womens Univ. Semi-supervised domain adaptation with multiple kernel learning
Hiroyuki Okada, Kuniaki Uehara (Kobe Univ.) IBISML2011-79		 We are interested in the problem of domain
adaptation，a branch of transfer learning. Traditional, unsupervised,
domain... [more]		 IBISML2011-79
pp.251-256
IBISML 2011-11-10
15:45		 Nara Nara Womens Univ. Effectiveness of Laplacian-based kernels from the hubness point of view
Ikumi Suzuki (NAIST), Kazuo Hara (NIG), Masashi Shimbo, Yuji Matsumoto (NAIST) IBISML2011-80		  [more] IBISML2011-80
pp.257-262
IBISML 2011-11-10
15:45		 Nara Nara Womens Univ. A Parametric Programming Approach for Outlier Detection and Robust Learning for Classification and Regression
Ichiro Takeuchi (NIT) IBISML2011-81		 We study outlier detection and robust learning problem for support vector machine (SVM). In the literature there are two... [more] IBISML2011-81
pp.263-269
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