## HomePage of Kazuho Watanabe

[Japanese]
Dept. of Computer Science and Engineering, Toyohashi University of Technology

e-mail: wkazuho <<p}p{>> cs.tut.ac.jp

CV,
Publications

--News--------------------------------------

WITMSE2017 (Paris, France, Sep. 11-13)

"Rate-distortion dimension and Bayesian learning coefficient"

The following two papers have been published in Entropy.

Projection to Mixture Families and Rate-Distortion Bounds with Power Distortion Measures

Special Issue "Information Geometry II", 19(6), 262, 2017.

Rate-Distortion Bounds for Kernel-Based Distortion Measures

Special Issue "Information Theory in Machine Learning and Data Science", 19(7), 336, 2017.

IEEE ISIT2017 (Aachen, Germany, Jun. 25-30)

"Rate-Distortion Tradeoffs under Kernel-Based Distortion Measures"

WITMSE2016 (Univ. of Helsinki, Finland, Sep. 19-21)

IEEE ITW2016 (Univ. of Cambridge, UK, Sep. 11-14)

"Constant-Width Rate-Distortion Bounds for Power Distortion Measures"

Also I am one of big fans of Prof. MacKay's book...

The following paper has been accepted to IEEE Trans. on Information Theory.

Kazuho Watanabe and Shiro Ikeda,

"Rate-Distortion Functions for Gamma-Type Sources under Absolute-Log Distortion Measure"

I made a presentation at HD3-2015 (Kyoto, Japan, Dec. 14-17).

I attended WITMSE2015 (Copenhagen, Denmark, June 24-26).

The following paper has been accepted to Neurocomputing:

Kazuho Watanabe, "Vector Quantization Based on Epsilon-Insensitive Mixture Models"

The following paper has been accepted to IEEE PacificVis 2015:

Kazuho Watanabe, Hsiang-Yun Wu, Yusuke Niibe, Shigeo Takahashi, and Issei Fujishiro,

"Biclustering Multivariate Data for Correlated Subspace Mining"

The following paper has been accepted to the Journal of Machine Learning Research:

Kazuho Watanabe and Teemu Roos,

"Achievability of Asymptotic Minimax Regret by Horizon-Dependent and Horizon-Independent Strategies"

NIPS2014: Shinichi Nakajima, Issei Sato, Masashi Sugiyama, Kazuho Watanabe, and Hiroko Kobayashi,

"Analysis of variational Bayesian latent Dirichlet allocation: weaker sparsity than MAP"

The following paper has been accepted to IEEE trans. on Neural Networks and Learning Systems:

Takuya Konishi, Takatomi Kubo, Kazuho Watanabe, and Kazushi Ikeda,

"Variational Bayesian inference algorithms for infinite relational model of network data"

The following paper has been accepted to Machine Learning journal:

Kazuho Watanabe and Shiro Ikeda,

"Entropic risk minimization for nonparametric estimation of mixing distributions"

iV2014: Koto Nohno, Hsiang-Yun Wu, Kazuho Watanabe, Shigeo Takahashi, and Issei Fujishiro,

"Spectral-based contractible parallel coordinates"

WITMSE2014: Kazuho Watanabe,

"Rate-Distortion Analysis for an Epsilon-Insensitive Loss Function"

ISIT2014: Andrew Barron, Teemu Roos, and Kazuho Watanabe,

"Bayesian Properties of Normalized Maximum Likelihood and its Fast Computation"

The following paper has been accepted to IEEE trans. on Neural Networks and Learning Systems:

Atsushi Miyamoto, Kazuho Watanabe, Kazushi Ikeda, and Masa-aki Sato,

"Variational inference with ARD prior for NIRS diffuse optical tomography"
--------------------------------------------

My former pages:

Nara Institute of Science and Technology(when I was an assistant prof)

The University of Tokyo(when I was a postdoc)

Tokyo Institute of Technology(when I was a graduate student)
Back to TUT-LISL

Otlichnyi tehnicheskii universitet esti tut, v Toyohashi.