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» Learning Bounds for Domain Adaptation
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ICML
2005
IEEE
16 years 4 months ago
Supervised versus multiple instance learning: an empirical comparison
We empirically study the relationship between supervised and multiple instance (MI) learning. Algorithms to learn various concepts have been adapted to the MI representation. Howe...
Soumya Ray, Mark Craven
121
Voted
ALT
2007
Springer
16 years 14 days ago
Pseudometrics for State Aggregation in Average Reward Markov Decision Processes
We consider how state similarity in average reward Markov decision processes (MDPs) may be described by pseudometrics. Introducing the notion of adequate pseudometrics which are we...
Ronald Ortner
122
Voted
ML
1998
ACM
102views Machine Learning» more  ML 1998»
15 years 3 months ago
Statistical Mechanics of Online Learning of Drifting Concepts: A Variational Approach
We review the application of statistical mechanics methods to the study of online learning of a drifting concept in the limit of large systems. The model where a feed-forward netwo...
Renato Vicente, Osame Kinouchi, Nestor Caticha
128
Voted
FGR
2008
IEEE
153views Biometrics» more  FGR 2008»
15 years 10 months ago
Facial image analysis using local feature adaptation prior to learning
Many facial image analysis methods rely on learningbased techniques such as Adaboost or SVMs to project classifiers based on the selection of local image filters (e.g., Haar and...
Rogerio Feris, Ying-li Tian, Yun Zhai, Arun Hampap...
138
Voted
CVPR
2010
IEEE
15 years 11 months ago
Visual Event Recognition in Videos by Learning from Web Data
We propose a visual event recognition framework for consumer domain videos by leveraging a large amount of loosely labeled web videos (e.g., from YouTube). First, we propose a new...
Lixin Duan, Dong Xu, Wai-Hung Tsang, Jiebo Luo