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UAI
1997
13 years 10 months ago
A Scheme for Approximating Probabilistic Inference
This paper describes a class ofprobabilistic approximation algorithms based on bucket elimination which o er adjustable levels of accuracy ande ciency. We analyzethe approximation...
Rina Dechter, Irina Rish
AAAI
2006
13 years 10 months ago
Point-based Dynamic Programming for DEC-POMDPs
We introduce point-based dynamic programming (DP) for decentralized partially observable Markov decision processes (DEC-POMDPs), a new discrete DP algorithm for planning strategie...
Daniel Szer, François Charpillet
ICASSP
2011
IEEE
13 years 12 days 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, ...
STOC
2004
ACM
129views Algorithms» more  STOC 2004»
14 years 9 months ago
Sorting and searching in the presence of memory faults (without redundancy)
We investigate the design of algorithms resilient to memory faults, i.e., algorithms that, despite the corruption of some memory values during their execution, are able to produce...
Irene Finocchi, Giuseppe F. Italiano
EMO
2005
Springer
68views Optimization» more  EMO 2005»
14 years 2 months ago
Multi-objective Optimization of Problems with Epistemic Uncertainty
Abstract. Multi-objective evolutionary algorithms (MOEAs) have proven to be a powerful tool for global optimization purposes of deterministic problem functions. Yet, in many real-w...
Philipp Limbourg