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» Quantizing Density Estimators
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NIPS
2007
13 years 9 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...
ICML
2008
IEEE
14 years 8 months ago
Tailoring density estimation via reproducing kernel moment matching
Moment matching is a popular means of parametric density estimation. We extend this technique to nonparametric estimation of mixture models. Our approach works by embedding distri...
Alex J. Smola, Arthur Gretton, Bernhard Schöl...
MVA
2007
149views Computer Vision» more  MVA 2007»
13 years 9 months ago
Extracting Object Regions Using Locally Estimated Probability Density Functions
In this paper, a novel method for estimating a precise object region using a given rough object region is proposed. For determining whether each pixel belongs to an object or not,...
Hidenori Takeshima, Takashi Ida, Toshimitsu Kaneko
ICASSP
2008
IEEE
14 years 2 months ago
On the tradeoff between security and Robustness of the Trellis Coded Quantization scheme
The steganographic security in the Cachin’s work is defined as the statistical invisibility between the host signal and its marked version. At contrary, the robustness to an at...
Sofiane Braci, Rémy Boyer, Claude Delpha
CGF
2010
174views more  CGF 2010»
13 years 7 months ago
Bidirectional Texture Function Compression Based on Multi-Level Vector Quantization
The Bidirectional Texture Function (BTF) is becoming widely used for accurate representation of real-world material appearance. In this paper a novel BTF compression model is prop...
Vlastimil Havran, J. Filip, Karol Myszkowski