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NIPS
2007
13 years 9 months ago
Bayesian Co-Training
We propose a Bayesian undirected graphical model for co-training, or more generally for semi-supervised multi-view learning. This makes explicit the previously unstated assumption...
Shipeng Yu, Balaji Krishnapuram, Rómer Rosa...
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...
ATAL
2007
Springer
14 years 1 months ago
Model-based function approximation in reinforcement learning
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Nicholas K. Jong, Peter Stone
TIP
2011
169views more  TIP 2011»
13 years 2 months ago
From Local Pixel Structure to Global Image Super-Resolution: A New Face Hallucination Framework
Abstract—We have developed a new face hallucination framework termed from local pixel structure to global image super-resolution (LPS-GIS). Based on the assumption that two simil...
Yu Hu, Kin-Man Lam, Guoping Qiu, Tingzhi Shen
ICML
1997
IEEE
13 years 12 months ago
A Comparative Study on Feature Selection in Text Categorization
This paper is a comparative study of feature selection methods in statistical learning of text categorization. The focus is on aggressive dimensionality reduction. Five methods we...
Yiming Yang, Jan O. Pedersen