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DEBU
2000
101views more  DEBU 2000»
15 years 2 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
PAMI
2007
187views more  PAMI 2007»
15 years 2 months ago
Supervised Learning of Semantic Classes for Image Annotation and Retrieval
—A probabilistic formulation for semantic image annotation and retrieval is proposed. Annotation and retrieval are posed as classification problems where each class is defined as...
Gustavo Carneiro, Antoni B. Chan, Pedro J. Moreno,...
IJCV
2010
152views more  IJCV 2010»
15 years 1 months ago
Learning Articulated Structure and Motion
Humans demonstrate a remarkable ability to parse complicated motion sequences into their constituent structures and motions. We investigate this problem, attempting to learn the st...
David A. Ross, Daniel Tarlow, Richard S. Zemel
IJAMCIGI
2010
90views more  IJAMCIGI 2010»
15 years 8 days ago
A Reinforcement Learning - Great-Deluge Hyper-Heuristic for Examination Timetabling
Hyper-heuristics are identified as the methodologies that search the space generated by a finite set of low level heuristics for solving difficult problems. One of the iterative h...
Ender Özcan, Mustafa Misir, Gabriela Ochoa, E...
CORR
2011
Springer
210views Education» more  CORR 2011»
14 years 10 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