337 search results - page 35 / 68 » An Anytime Algorithm for Decision Making under Uncertainty |
100
Voted
ICASSP
2011
IEEE
14 years 7 months ago
2011
IEEE
Commonly used speech enhancement algorithms estimate the power spectral density of the noise to be removed, or make a decision about the presence of speech in a particular frame, ...
138
Voted
CCE
2004
15 years 3 months ago
2004
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...
121
Voted
ICRA
2008
IEEE
15 years 10 months ago
2008
IEEE
— Target tracking has two variants that are often studied independently with different approaches: target searching requires a robot to find a target initially not visible, and ...
149
Voted
COCO
1995
Springer
15 years 7 months ago
1995
Springer
For the worst-case complexity measure, if P = NP, then P = OptP, i.e., all NP optimization problems are polynomial-time solvable. On the other hand, it is not clear whether a simi...
146
Voted
AAAI
2006
15 years 4 months ago
2006
Partially observable Markov decision processes (POMDPs) are an intuitive and general way to model sequential decision making problems under uncertainty. Unfortunately, even approx...