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- Publications
- Influence
Database retrieval for similar images using ICA and PCA bases
- Naoto Katsumata, Y. Matsuyama
- Computer Science
- Eng. Appl. Artif. Intell.
- 1 September 2005
TLDR
Independent Component Analysis Minimizing Convex Divergence
- Y. Matsuyama, Naoto Katsumata, R. Kawamura
- Mathematics, Computer Science
- ICANN
- 26 June 2003
TLDR
Towards the Unification of Human Movement, Animation and Humanoid in the Network
- Y. Matsuyama, Satoshi Yoshinaga, +6 authors Naoto Katsumata
- Computer Science
- ICONIP
- 22 November 2004
TLDR
/spl alpha/-EM algorithm and /spl alpha/-ICA learning based upon extended logarithmic information measures
- Y. Matsuyama, Takeshi Niimoto, Naoto Katsumata, Y. Suzuki, S. Furukawa
- Mathematics, Computer Science
- Proceedings of the IEEE-INNS-ENNS International…
- 27 July 2000
TLDR
Retrieval-Aware Image Compression, Its Format and Viewer Based Upon Learned Bases
- Naoto Katsumata, Y. Matsuyama, +4 authors T. Nakamura
- Computer Science
- ICONIP
- 3 October 2006
TLDR
Optimization transfer for computational learning: a hierarchy from f-ICA and alpha-EM to their offsprings
- Y. Matsuyama, S. Imahara, Naoto Katsumata
- Mathematics
- Proceedings of the International Joint…
- 7 August 2002
TLDR
Independent Component Analysis Using Convex Divergence
The convex divergence is used as a surrogate function for obtaining a class of ICA algorithms (Independent Component Analysis) called the f-ICA. The convex divergence is a super class of… Expand
- 3
- PDF
Evaluation of Energy Consumption of Ice Thermal Storage Type Packaged Air Conditioners
- Sachio Sekiya, Naoto Katsumata, Takao Senshu
- Environmental Science
- 2003
INDEPENDENT COMPONENT ANALYSIS WITH JOINT SPEEDUP AND SUPERVISORY CONCEPT INJECTION : APPLICATIONS TO BRAIN fMRI MAP DISTILLATION
Methods to combine speedup terms and supervisory concept injection are presented. The speedup is based upon iterative optimization of the convex divergence. The injection of supervisory information… Expand
Image-to-Image Retrieval Using Computationally Learned Bases and Color Information
- Y. Matsuyama, Fuminori Ohashi, +4 authors Y. Hoshino
- Computer Science
- International Joint Conference on Neural Networks
- 29 October 2007
TLDR