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DEBU
2000
101views more  DEBU 2000»
13 years 10 months ago
Learning to Understand the Web
In a traditional information retrieval system, it is assumed that queries can be posed about any topic. In reality, a large fraction of web queries are posed about a relatively sm...
William W. Cohen, Andrew McCallum, Dallan Quass
IVC
2007
97views more  IVC 2007»
13 years 10 months ago
Stochastic exploration and active learning for image retrieval
This paper deals with content-based image retrieval. When the user is looking for large categories, statistical classification techniques are efficient as soon as the training se...
Matthieu Cord, Philippe Henri Gosselin, Sylvie Phi...
CORR
2011
Springer
210views Education» more  CORR 2011»
13 years 5 months ago
Online Learning of Rested and Restless Bandits
In this paper we study the online learning problem involving rested and restless multiarmed bandits with multiple plays. The system consists of a single player/user and a set of K...
Cem Tekin, Mingyan Liu
CVPR
2011
IEEE
13 years 2 months ago
Learning People Detection Models from Few Training Samples
People detection is an important task for a wide range of applications in computer vision. State-of-the-art methods learn appearance based models requiring tedious collection and ...
Leonid Pishchulin, Christian Wojek, Arjun Jain, Th...
ICASSP
2011
IEEE
13 years 2 months ago
Maximum marginal likelihood estimation for nonnegative dictionary learning
We describe an alternative to standard nonnegative matrix factorisation (NMF) for nonnegative dictionary learning. NMF with the Kullback-Leibler divergence can be seen as maximisa...
Onur Dikmen, Cédric Févotte