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CCE
2004
13 years 7 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»
13 years 6 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
11 years 9 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
12 years 11 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
14 years 1 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