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NIPS
2003
13 years 9 months ago
Gaussian Processes in Reinforcement Learning
We exploit some useful properties of Gaussian process (GP) regression models for reinforcement learning in continuous state spaces and discrete time. We demonstrate how the GP mod...
Carl Edward Rasmussen, Malte Kuss
ICML
2010
IEEE
13 years 8 months ago
Convergence of Least Squares Temporal Difference Methods Under General Conditions
We consider approximate policy evaluation for finite state and action Markov decision processes (MDP) in the off-policy learning context and with the simulation-based least square...
Huizhen Yu
GLOBECOM
2008
IEEE
13 years 7 months ago
Nonlinear Quadratic Pricing for Concavifiable Utilities in Network Rate Control
This paper deals with a category of concavifiable functions that can be used to model inelastic traffic in the network. Such class of functions can be concavified within an interva...
Quanyan Zhu, Raouf Boutaba
ICDM
2005
IEEE
161views Data Mining» more  ICDM 2005»
14 years 1 months ago
Making Logistic Regression a Core Data Mining Tool with TR-IRLS
Binary classification is a core data mining task. For large datasets or real-time applications, desirable classifiers are accurate, fast, and need no parameter tuning. We presen...
Paul Komarek, Andrew W. Moore
SIAMMAX
2010
189views more  SIAMMAX 2010»
13 years 2 months ago
Fast Algorithms for the Generalized Foley-Sammon Discriminant Analysis
Linear Discriminant Analysis (LDA) is one of the most popular approaches for feature extraction and dimension reduction to overcome the curse of the dimensionality of the high-dime...
Lei-Hong Zhang, Li-Zhi Liao, Michael K. Ng