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AAAI
2012
13 years 6 days ago
Kernel-Based Reinforcement Learning on Representative States
Markov decision processes (MDPs) are an established framework for solving sequential decision-making problems under uncertainty. In this work, we propose a new method for batchmod...
Branislav Kveton, Georgios Theocharous
ICANN
2005
Springer
15 years 3 months ago
Informational Energy Kernel for LVQ
We describe a kernel method which uses the maximization of Onicescu’s informational energy as a criteria for computing the relevances of input features. This adaptive relevance d...
Angel Cataron, Razvan Andonie
CLUSTER
2008
IEEE
15 years 4 months ago
SPRAT: Runtime processor selection for energy-aware computing
—A commodity personal computer (PC) can be seen as a hybrid computing system equipped with two different kinds of processors, i.e. CPU and a graphics processing unit (GPU). Since...
Hiroyuki Takizawa, Katsuto Sato, Hiroaki Kobayashi
CVPR
2005
IEEE
15 years 11 months ago
Kernel-Based Bayesian Filtering for Object Tracking
Particle filtering provides a general framework for propagating probability density functions in non-linear and non-Gaussian systems. However, the algorithm is based on a Monte Ca...
Bohyung Han, Ying Zhu, Dorin Comaniciu, Larry S. D...
PODS
2008
ACM
153views Database» more  PODS 2008»
15 years 10 months ago
Approximation algorithms for co-clustering
Co-clustering is the simultaneous partitioning of the rows and columns of a matrix such that the blocks induced by the row/column partitions are good clusters. Motivated by severa...
Aris Anagnostopoulos, Anirban Dasgupta, Ravi Kumar