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SIGPRO
2010
111views more  SIGPRO 2010»
12 years 11 months ago
Semi-supervised speaker identification under covariate shift
In this paper, we propose a novel semi-supervised speaker identification method that can alleviate the influence of non-stationarity such as session dependent variation, the recor...
Makoto Yamada, Masashi Sugiyama, Tomoko Matsui
IEICET
2011
12 years 11 months ago
Lighting Condition Adaptation for Perceived Age Estimation
Over the recent years, a great deal of effort has been made to age estimation from face images. It has been reported that age can be accurately estimated under controlled environ...
Kazuya Ueki, Masashi Sugiyama, Yasuyuki Ihara
ICASSP
2010
IEEE
13 years 4 months ago
Automatic audio tagging using covariate shift adaptation
Automatically annotating or tagging unlabeled audio files has several applications, such as database organization and recommender systems. We are interested in the case where the...
Gordon Wichern, Makoto Yamada, Harvey D. Thornburg...
NIPS
2007
13 years 6 months ago
Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation
A situation where training and test samples follow different input distributions is called covariate shift. Under covariate shift, standard learning methods such as maximum likeli...
Masashi Sugiyama, Shinichi Nakajima, Hisashi Kashi...
SDM
2008
SIAM
134views Data Mining» more  SDM 2008»
13 years 6 months ago
Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation
Covariate shift is a situation in supervised learning where training and test inputs follow different distributions even though the functional relation remains unchanged. A common...
Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Steffen...