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Information Geometry of U-Boost and Bregman Divergence

JOURNAL ARTICLE published 1 July 2004 in Neural Computation

Authors: Noboru Murata | Takashi Takenouchi | Takafumi Kanamori | Shinto Eguchi

Robust Loss Functions for Boosting

JOURNAL ARTICLE published August 2007 in Neural Computation

Authors: Takafumi Kanamori | Takashi Takenouchi | Shinto Eguchi | Noboru Murata

Robust Boosting Algorithm Against Mislabeling in Multiclass Problems

JOURNAL ARTICLE published June 2008 in Neural Computation

Authors: Takashi Takenouchi | Shinto Eguchi | Noboru Murata | Takafumi Kanamori

The Most Robust Loss Function for Boosting

BOOK CHAPTER published 2004 in Neural Information Processing

Authors: Takafumi Kanamori | Takashi Takenouchi | Shinto Eguchi | Noboru Murata

Robustifying AdaBoost by Adding the Naive Error Rate

JOURNAL ARTICLE published 1 April 2004 in Neural Computation

Authors: Takashi Takenouchi | Shinto Eguchi

Graph-based composite local Bregman divergences on discrete sample spaces

JOURNAL ARTICLE published November 2017 in Neural Networks

Research funded by JSPS (15H01678,16K00044,25730018,16K00051)

Authors: Takafumi Kanamori | Takashi Takenouchi

Stochastic Reasoning, Free Energy, and Information Geometry

JOURNAL ARTICLE published 1 September 2004 in Neural Computation

Authors: Shiro Ikeda | Toshiyuki Tanaka | Shun-ichi Amari

Divergence Function, Duality, and Convex Analysis

JOURNAL ARTICLE published 1 January 2004 in Neural Computation

Authors: Jun Zhang

An Extension of the Receiver Operating Characteristic Curve and AUC-Optimal Classification

JOURNAL ARTICLE published October 2012 in Neural Computation

Authors: Takashi Takenouchi | Osamu Komori | Shinto Eguchi

Robust Blind Source Separation by Beta Divergence

JOURNAL ARTICLE published 1 August 2002 in Neural Computation

Authors: Minami Mihoko | Shinto Eguchi

Spontaneous Clustering via Minimum Gamma-Divergence

JOURNAL ARTICLE published February 2014 in Neural Computation

Authors: Akifumi Notsu | Osamu Komori | Shinto Eguchi

Information Divergence Geometry and the Application to Statistical Machine Learning

BOOK CHAPTER published in Information Theory and Statistical Learning

Authors: Shinto Eguchi

Binary classifiers ensemble based on Bregman divergence for multi-class classification

JOURNAL ARTICLE published January 2018 in Neurocomputing

Authors: Takashi Takenouchi | Shin Ishii

Improving Generalization Performance of Natural Gradient Learning Using Optimized Regularization by NIC

JOURNAL ARTICLE published 1 February 2004 in Neural Computation

Authors: Hyeyoung Park | Noboru Murata | Shun-ichi Amari

Information Geometry

BOOK CHAPTER published 2022 in Minimum Divergence Methods in Statistical Machine Learning

Authors: Shinto Eguchi | Osamu Komori

Investigation of Possible Neural Architectures Underlying Information-Geometric Measures

JOURNAL ARTICLE published 1 April 2004 in Neural Computation

Authors: Masami Tatsuno | Masato Okada

Minimum information divergence of Q-functions for dynamic treatment resumes

JOURNAL ARTICLE published January 2024 in Information Geometry

Research funded by JSPS KAKENHI (18H03211)

Authors: Shinto Eguchi

Enhancement of Information Transmission Efficiency by Synaptic Failures

JOURNAL ARTICLE published 1 June 2004 in Neural Computation

Authors: Mark S. Goldman

How Many Clusters? An Information-Theoretic Perspective

JOURNAL ARTICLE published 1 December 2004 in Neural Computation

Authors: Susanne Still | William Bialek

Information Geometry for Covariance Estimation in Heterogeneous Clutter with Total Bregman Divergence

JOURNAL ARTICLE published 8 April 2018 in Entropy

Authors: Xiaoqiang Hua | Yongqiang Cheng | Hongqiang Wang | Yuliang Qin