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ECML
2007
Springer
15 years 9 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
TROB
2002
88views more  TROB 2002»
15 years 5 months ago
Gripper point contacts for part alignment
-- The initial resting pose of many industrial parts differs from the orientation desired for assembly. We show that it is possible to align parts during grasping using a standard ...
Mike Tao Zhang, Ken Goldberg
ICASSP
2011
IEEE
14 years 9 months ago
Empirical divergence maximization for quantizer design: An analysis of approximation error
Empirical divergence maximization is an estimation method similar to empirical risk minimization whereby the Kullback-Leibler divergence is maximized over a class of functions tha...
Michael A. Lexa
NSDI
2008
15 years 8 months ago
cSamp: A System for Network-Wide Flow Monitoring
Critical network management applications increasingly demand fine-grained flow level measurements. However, current flow monitoring solutions are inadequate for many of these appl...
Vyas Sekar, Michael K. Reiter, Walter Willinger, H...
TCS
2010
15 years 4 months ago
Active learning in heteroscedastic noise
We consider the problem of actively learning the mean values of distributions associated with a finite number of options. The decision maker can select which option to generate t...
András Antos, Varun Grover, Csaba Szepesv&a...