Presentation | 2014-11-17 Online Direct Density-ratio Estimation under the Kullback-Leibler Loss PLESSIS Marthinus Christoffel DU, Hiroaki SHIINO, Masashi SUGIYAMA, |
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Abstract(in English) | Many machine learning problems, such as non-stationarity adaptation, outlier detection, dimensionality reduction, and conditional density estimation, can be effectively solved by using the ratio of probability densities. Since the naive two step procedure of first estimating the probability densities and then taking their ratio performs poorly, methods to directly estimate the density ratio from two sets of samples without density estimation have been extensively studied recently. However, these methods are batch algorithms that use the whole dataset to estimate the density ratio, and they are inefficient in the online setup where training samples are provided sequentially and solutions are updated incrementally without storing previous samples. In this paper, we propose an online version of a density ratio estimator based on the adaptive regularization of weight vectors (AROW). Through experiments on inlier-based outlier detection, we demonstrate the usefulness of the proposed method. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | online learning / density-ratio estimation / adaptive regularization of weight vectors / outlier detection |
Paper # | IBISML2014-59 |
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Committee | IBISML |
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Conference Date | 2014/11/10(1days) |
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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) | Online Direct Density-ratio Estimation under the Kullback-Leibler Loss |
Sub Title (in English) | |
Keyword(1) | online learning |
Keyword(2) | density-ratio estimation |
Keyword(3) | adaptive regularization of weight vectors |
Keyword(4) | outlier detection |
1st Author's Name | PLESSIS Marthinus Christoffel DU |
1st Author's Affiliation | Department of Complexity Science and Engineering, University of Tokyo() |
2nd Author's Name | Hiroaki SHIINO |
2nd Author's Affiliation | Department of Computer Science, Tokyo Institute of Technology |
3rd Author's Name | Masashi SUGIYAMA |
3rd Author's Affiliation | Department of Complexity Science and Engineering, University of Tokyo |
Date | 2014-11-17 |
Paper # | IBISML2014-59 |
Volume (vol) | vol.114 |
Number (no) | 306 |
Page | pp.pp.- |
#Pages | 6 |
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