| Presentation | 2011-03-29 Information-Maximization Clustering : Analytic Solution and Model Selection Masashi SUGIYAMA, Makoto YAMADA, Manabu KIMURA, Hirotaka HACHIYA, |
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| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | A recently-proposed information-maximization clustering method (Gomes et al., NIPS2010) learns a kernel logistic regression classifier in an unsupervised manner so that mutual information between feature vectors and cluster assignments is maximized. A notable advantage of this approach is that it only involves continuous optimization of a logistic model, which is substantially easier than discrete optimization of cluster assignments. However, this method still suffers from two weaknesses: (i) manual tuning of kernel parameters is necessary, and (ii) finding a good local optimal solution is not straightforward due to the strong non-convexity of logistic-regression learning. In this paper, we first show that the kernel parameters can be systematically optimized by maximizing mutual information estimates. We then propose an alternative information-maximization clustering approach using a squared-loss variant of mutual information. This novel approach allows us to obtain clustering solutions analytically in a computationally very efficient way. Through experiments, we demonstrate the usefulness of the proposed approaches. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Clustering / Information Maximization / Squared-Loss Mutual Information |
| Paper # | IBISML2010-114 |
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| Conference Information | |
| Committee | IBISML |
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| Conference Date | 2011/3/21(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Information-Based Induction Sciences and Machine Learning (IBISML) |
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| Language | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Information-Maximization Clustering : Analytic Solution and Model Selection |
| Sub Title (in English) | |
| Keyword(1) | Clustering |
| Keyword(2) | Information Maximization |
| Keyword(3) | Squared-Loss Mutual Information |
| 1st Author's Name | Masashi SUGIYAMA |
| 1st Author's Affiliation | Department of Computer Science, Tokyo Institute of Technology() |
| 2nd Author's Name | Makoto YAMADA |
| 2nd Author's Affiliation | Department of Computer Science, Tokyo Institute of Technology |
| 3rd Author's Name | Manabu KIMURA |
| 3rd Author's Affiliation | Department of Computer Science, Tokyo Institute of Technology |
| 4th Author's Name | Hirotaka HACHIYA |
| 4th Author's Affiliation | Department of Computer Science, Tokyo Institute of Technology |
| Date | 2011-03-29 |
| Paper # | IBISML2010-114 |
| Volume (vol) | vol.110 |
| Number (no) | 476 |
| Page | pp.pp.- |
| #Pages | 8 |
| Date of Issue | |