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CVPR
2010
IEEE
15 years 2 months ago
P-N learning: Bootstrapping binary classifiers by structural constraints
This paper shows that the performance of a binary classifier can be significantly improved by the processing of structured unlabeled data, i.e. data are structured if knowing the ...
Zdenek Kalal, Jiri Matas, Krystian Mikolajczyk
NN
2008
Springer
15 years 4 months ago
Multilayer in-place learning networks for modeling functional layers in the laminar cortex
Currently, there is a lack of general-purpose in-place learning networks that model feature layers in the cortex. By "general-purpose" we mean a general yet adaptive hig...
Juyang Weng, Tianyu Luwang, Hong Lu, Xiangyang Xue
IWANN
1999
Springer
15 years 9 months ago
Using Temporal Neighborhoods to Adapt Function Approximators in Reinforcement Learning
To avoid the curse of dimensionality, function approximators are used in reinforcement learning to learn value functions for individual states. In order to make better use of comp...
R. Matthew Kretchmar, Charles W. Anderson
CVPR
2005
IEEE
16 years 6 months ago
Unsupervised Learning of Discriminative Edge Measures for Vehicle Matching between Non-Overlapping Cameras
This paper proposes a novel method for matching road vehicles between two non-overlapping cameras. The matching problem is formulated as a same-different classification problem: p...
Ying Shan, Harpreet S. Sawhney, Rakesh Kumar
CDC
2008
IEEE
142views Control Systems» more  CDC 2008»
15 years 11 months ago
Convergence of rule-of-thumb learning rules in social networks
— We study the problem of dynamic learning by a social network of agents. Each agent receives a signal about an underlying state and communicates with a subset of agents (his nei...
Daron Acemoglu, Angelia Nedic, Asuman E. Ozdaglar