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» Learning Algorithms for Domain Adaptation
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124
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NIPS
2004
15 years 1 months ago
Maximising Sensitivity in a Spiking Network
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
Anthony J. Bell, Lucas C. Parra
JMLR
2011
148views more  JMLR 2011»
14 years 7 months ago
Multitask Sparsity via Maximum Entropy Discrimination
A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
Tony Jebara
COMPGEOM
2008
ACM
15 years 2 months ago
Maximum thick paths in static and dynamic environments
We consider the problem of finding a maximum number of disjoint paths for unit disks moving amidst static or dynamic obstacles. For the static case we give efficient exact algorit...
Esther M. Arkin, Joseph S. B. Mitchell, Valentin P...
ICIP
2003
IEEE
16 years 2 months ago
Feature selection for unsupervised discovery of statistical temporal structures in video
We present algorithms for automatic feature selection for unsupervised structure discovery from video sequences. Feature selection in this scenario is hard because of the absence ...
Lexing Xie, Shih-Fu Chang, Ajay Divakaran, Huifang...
106
Voted
WWW
2009
ACM
16 years 1 months ago
Extracting article text from the web with maximum subsequence segmentation
Much of the information on the Web is found in articles from online news outlets, magazines, encyclopedias, review collections, and other sources. However, extracting this content...
Jeff Pasternack, Dan Roth