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» Preference learning with Gaussian processes
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NIPS
1997
13 years 8 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
AMR
2005
Springer
117views Multimedia» more  AMR 2005»
14 years 29 days 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
14 years 9 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...
ICASSP
2011
IEEE
12 years 11 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...
SDM
2012
SIAM
294views Data Mining» more  SDM 2012»
11 years 9 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...