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» Local and Global Comparison of Continuous Functions
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ECML
2007
Springer
13 years 11 months ago
Efficient Continuous-Time Reinforcement Learning with Adaptive State Graphs
Abstract. We present a new reinforcement learning approach for deterministic continuous control problems in environments with unknown, arbitrary reward functions. The difficulty of...
Gerhard Neumann, Michael Pfeiffer, Wolfgang Maass
JMIV
2007
156views more  JMIV 2007»
13 years 7 months ago
Using the Shape Gradient for Active Contour Segmentation: from the Continuous to the Discrete Formulation
A variational approach to image or video segmentation consists in defining an energy depending on local or global image characteristics, the minimum of which being reached for ob...
Eric Debreuve, Muriel Gastaud, Michel Barlaud, Gil...
NIPS
2007
13 years 9 months ago
Random Sampling of States in Dynamic Programming
We combine three threads of research on approximate dynamic programming: sparse random sampling of states, value function and policy approximation using local models, and using lo...
Christopher G. Atkeson, Benjamin Stephens
MP
2007
89views more  MP 2007»
13 years 7 months ago
Globally convergent limited memory bundle method for large-scale nonsmooth optimization
Many practical optimization problems involve nonsmooth (that is, not necessarily differentiable) functions of thousands of variables. In the paper [Haarala, Miettinen, M¨akel¨a,...
Napsu Haarala, Kaisa Miettinen, Marko M. Mäke...
ICPR
2008
IEEE
14 years 1 months ago
Comparison of Particle Swarm Optimization and Genetic Algorithm for HMM training
Hidden Markov Model (HMM) is the dominant technology in speech recognition. The problem of optimizing model parameters is of great interest to the researchers in this area. The Ba...
Fengqin Yang, Changhai Zhang, Tieli Sun