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JMLR
2006
125views more  JMLR 2006»
14 years 11 months ago
Efficient Learning of Label Ranking by Soft Projections onto Polyhedra
We discuss the problem of learning to rank labels from a real valued feedback associated with each label. We cast the feedback as a preferences graph where the nodes of the graph ...
Shai Shalev-Shwartz, Yoram Singer
CORR
2010
Springer
105views Education» more  CORR 2010»
14 years 10 months ago
Optimism in Reinforcement Learning Based on Kullback-Leibler Divergence
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
Sarah Filippi, Olivier Cappé, Aurelien Gari...
JMLR
2010
149views more  JMLR 2010»
14 years 6 months ago
Learning Bayesian Network Structure using LP Relaxations
We propose to solve the combinatorial problem of finding the highest scoring Bayesian network structure from data. This structure learning problem can be viewed as an inference pr...
Tommi Jaakkola, David Sontag, Amir Globerson, Mari...
ICCV
2011
IEEE
13 years 11 months ago
Optical Flow Estimation Using Learned Sparse Model
Optical flow estimation is a fundamental and ill-posed problem in computer vision. To recover a dense flow field, appropriate spatial constraints have to be enforced. Recent ad...
Kui Jia, Xiaogang Wang, Xiaoou Tang
JMLR
2006
124views more  JMLR 2006»
14 years 11 months ago
A Direct Method for Building Sparse Kernel Learning Algorithms
Many kernel learning algorithms, including support vector machines, result in a kernel machine, such as a kernel classifier, whose key component is a weight vector in a feature sp...
Mingrui Wu, Bernhard Schölkopf, Gökhan H...