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COLT
2008
Springer
13 years 10 months ago
Finding Metric Structure in Information Theoretic Clustering
We study the problem of clustering discrete probability distributions with respect to the Kullback-Leibler (KL) divergence. This problem arises naturally in many applications. Our...
Kamalika Chaudhuri, Andrew McGregor
ALT
2007
Springer
14 years 2 months ago
On Universal Transfer Learning
In transfer learning the aim is to solve new learning tasks using fewer examples by using information gained from solving related tasks. Existing transfer learning methods have be...
M. M. Hassan Mahmud
AGENTS
1998
Springer
14 years 27 days ago
Learning Situation-Dependent Costs: Improving Planning from Probabilistic Robot Execution
Physical domains are notoriously hard to model completely and correctly, especially to capture the dynamics of the environment. Moreover, since environments change, it is even mor...
Karen Zita Haigh, Manuela M. Veloso
ICCV
2009
IEEE
15 years 1 months ago
Is that you? Metric Learning Approaches for Face Identification
Face identification is the problem of determining whether two face images depict the same person or not. This is difficult due to variations in scale, pose, lighting, background...
Matthieu Guillaumin, Jakob Verbeek, Cordelia Schmi...
NECO
2010
103views more  NECO 2010»
13 years 7 months ago
Posterior Weighted Reinforcement Learning with State Uncertainty
Reinforcement learning models generally assume that a stimulus is presented that allows a learner to unambiguously identify the state of nature, and the reward received is drawn f...
Tobias Larsen, David S. Leslie, Edmund J. Collins,...