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FOCS
2006
IEEE
14 years 2 months ago
Near-Optimal Hashing Algorithms for Approximate Nearest Neighbor in High Dimensions
We present an algorithm for the c-approximate nearest neighbor problem in a d-dimensional Euclidean space, achieving query time of O(dn1/c2 +o(1) ) and space O(dn + n1+1/c2 +o(1) ...
Alexandr Andoni, Piotr Indyk
CORR
2010
Springer
146views Education» more  CORR 2010»
13 years 8 months ago
Adaptive Submodularity: A New Approach to Active Learning and Stochastic Optimization
Solving stochastic optimization problems under partial observability, where one needs to adaptively make decisions with uncertain outcomes, is a fundamental but notoriously diffic...
Daniel Golovin, Andreas Krause
AAAI
1994
13 years 9 months ago
Acting Optimally in Partially Observable Stochastic Domains
In this paper, we describe the partially observable Markov decision process pomdp approach to nding optimal or near-optimal control strategies for partially observable stochastic ...
Anthony R. Cassandra, Leslie Pack Kaelbling, Micha...
GECCO
2007
Springer
193views Optimization» more  GECCO 2007»
14 years 2 months ago
Approximating covering problems by randomized search heuristics using multi-objective models
The main aim of randomized search heuristics is to produce good approximations of optimal solutions within a small amount of time. In contrast to numerous experimental results, th...
Tobias Friedrich, Nils Hebbinghaus, Frank Neumann,...
ICASSP
2011
IEEE
12 years 11 months ago
Stochastic resource allocation for cognitive radio networks based on imperfect state information
Efficient design of cognitive radio networks calls for secondary users implementing adaptive resource allocation, which requires knowledge of the channel state information in ord...
Antonio G. Marqués, Georgios B. Giannakis, ...