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ICML
2009
IEEE
16 years 7 months ago
Multi-class image segmentation using conditional random fields and global classification
A key aspect of semantic image segmentation is to integrate local and global features for the prediction of local segment labels. We present an approach to multi-class segmentatio...
Nils Plath, Marc Toussaint, Shinichi Nakajima
ICML
2009
IEEE
16 years 7 months ago
On sampling-based approximate spectral decomposition
This paper addresses the problem of approximate singular value decomposition of large dense matrices that arises naturally in many machine learning applications. We discuss two re...
Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar
ICML
2007
IEEE
16 years 7 months ago
Sparse probabilistic classifiers
The scores returned by support vector machines are often used as a confidence measures in the classification of new examples. However, there is no theoretical argument sustaining ...
Romain Hérault, Yves Grandvalet
ICML
2008
IEEE
16 years 7 months ago
Learning all optimal policies with multiple criteria
We describe an algorithm for learning in the presence of multiple criteria. Our technique generalizes previous approaches in that it can learn optimal policies for all linear pref...
Leon Barrett, Srini Narayanan
ICML
2005
IEEE
16 years 7 months ago
Bayesian sparse sampling for on-line reward optimization
We present an efficient "sparse sampling" technique for approximating Bayes optimal decision making in reinforcement learning, addressing the well known exploration vers...
Tao Wang, Daniel J. Lizotte, Michael H. Bowling, D...