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CCE
2004
14 years 11 months ago
An algorithmic framework for improving heuristic solutions: Part II. A new version of the stochastic traveling salesman problem
The algorithmic framework developed for improving heuristic solutions of the new version of deterministic TSP [Choi et al., 2002] is extended to the stochastic case. To verify the...
Jaein Choi, Jay H. Lee, Matthew J. Realff
ICRA
2010
IEEE
133views Robotics» more  ICRA 2010»
14 years 10 months ago
Variable resolution decomposition for robotic navigation under a POMDP framework
— Partially Observable Markov Decision Processes (POMDPs) offer a powerful mathematical framework for making optimal action choices in noisy and/or uncertain environments, in par...
Robert Kaplow, Amin Atrash, Joelle Pineau
CVPR
2012
IEEE
13 years 2 months ago
RALF: A reinforced active learning formulation for object class recognition
Active learning aims to reduce the amount of labels required for classification. The main difficulty is to find a good trade-off between exploration and exploitation of the lab...
Sandra Ebert, Mario Fritz, Bernt Schiele
ICASSP
2011
IEEE
14 years 3 months ago
Reinforcement learning for energy-efficient wireless transmission
We consider the problem of energy-efficient point-to-point transmission of delay-sensitive data (e.g. multimedia data) over a fading channel. We propose a rigorous and unified fra...
Nicholas Mastronarde, Mihaela van der Schaar
ICIP
2008
IEEE
15 years 6 months ago
A new theoretic framework for cross-layer optimization
Cross-layer optimization aims at improving the performance of network users operating in a time-varying, error-prone wireless environment. However, current solutions often rely on...
Fangwen Fu, Mihaela van der Schaar