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ICML
2004
IEEE
16 years 4 months ago
A needle in a haystack: local one-class optimization
This paper addresses the problem of finding a small and coherent subset of points in a given data. This problem, sometimes referred to as one-class or set covering, requires to fi...
Koby Crammer, Gal Chechik
131
Voted
ECML
2006
Springer
15 years 7 months ago
Approximate Policy Iteration for Closed-Loop Learning of Visual Tasks
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
Sébastien Jodogne, Cyril Briquet, Justus H....
125
Voted
ICMCS
2009
IEEE
153views Multimedia» more  ICMCS 2009»
15 years 1 months ago
Advertising based on users' photos
In this paper, we tackle the problem of learning a user's interest from his photo collections and suggesting relevant ads. We address two key challenges in this work: 1) unde...
Xin-Jing Wang, Mo Yu, Lei Zhang 0001, Wei-Ying Ma
IBPRIA
2007
Springer
15 years 9 months ago
Bayesian Hyperspectral Image Segmentation with Discriminative Class Learning
Abstract. This paper presents a new Bayesian approach to hyperspectral image segmentation that boosts the performance of the discriminative classifiers. This is achieved by combin...
Janete S. Borges, José M. Bioucas-Dias, And...
140
Voted
ATAL
2010
Springer
15 years 3 months ago
PAC-MDP learning with knowledge-based admissible models
PAC-MDP algorithms approach the exploration-exploitation problem of reinforcement learning agents in an effective way which guarantees that with high probability, the algorithm pe...
Marek Grzes, Daniel Kudenko