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» Preference learning with Gaussian processes
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119
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NIPS
1997
15 years 4 months ago
Nonlinear Markov Networks for Continuous Variables
We address the problem of learning structure in nonlinear Markov networks with continuous variables. This can be viewed as non-Gaussian multidimensional density estimation exploit...
Reimar Hofmann, Volker Tresp
111
Voted
AMR
2005
Springer
117views Multimedia» more  AMR 2005»
15 years 8 months ago
Learning User Queries in Multimodal Dissimilarity Spaces
Abstract. Different strategies to learn user semantic queries from dissimilarity representations of video audio-visual content are presented. When dealing with large corpora of vi...
Eric Bruno, Nicolas Moënne-Loccoz, Sté...
ECCV
2008
Springer
16 years 4 months ago
Learning Two-View Stereo Matching
We propose a graph-based semi-supervised symmetric matching framework that performs dense matching between two uncalibrated wide-baseline images by exploiting the results of sparse...
Jianxiong Xiao, Jingni Chen, Dit-Yan Yeung, Long Q...
128
Voted
ICASSP
2011
IEEE
14 years 6 months ago
An acoustically-motivated spatial prior for under-determined reverberant source separation
We consider the task of under-determined reverberant audio source separation. We model the contribution of each source to all mixture channels in the time-frequency domain as a ze...
Ngoc Q. K. Duong, Emmanuel Vincent, Rémi Gr...
164
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SDM
2012
SIAM
294views Data Mining» more  SDM 2012»
13 years 5 months ago
Kernelized Probabilistic Matrix Factorization: Exploiting Graphs and Side Information
We propose a new matrix completion algorithm— Kernelized Probabilistic Matrix Factorization (KPMF), which effectively incorporates external side information into the matrix fac...
Tinghui Zhou, Hanhuai Shan, Arindam Banerjee, Guil...