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» Approximate algorithms for neural-Bayesian approaches
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NIPS
2007
14 years 11 months ago
Theoretical Analysis of Heuristic Search Methods for Online POMDPs
Planning in partially observable environments remains a challenging problem, despite significant recent advances in offline approximation techniques. A few online methods have a...
Stéphane Ross, Joelle Pineau, Brahim Chaib-...
PVLDB
2008
111views more  PVLDB 2008»
14 years 9 months ago
Approximate lineage for probabilistic databases
In probabilistic databases, lineage is fundamental to both query processing and understanding the data. Current systems s.a. Trio or Mystiq use a complete approach in which the li...
Christopher Ré, Dan Suciu
NIPS
2007
14 years 11 months ago
Agreement-Based Learning
The learning of probabilistic models with many hidden variables and nondecomposable dependencies is an important and challenging problem. In contrast to traditional approaches bas...
Percy Liang, Dan Klein, Michael I. Jordan
ICASSP
2008
IEEE
15 years 4 months ago
Low-rank covariance matrix tapering for robust adaptive beamforming
Covariance matrix tapering (CMT) is a popular approach to improve the robustness of adaptive beamformers against moving or wideband interferers. In this paper, we develop a comput...
Michael Rübsamen, Christian Gerlach, Alex B. ...
TIP
2002
116views more  TIP 2002»
14 years 9 months ago
Adaptive approximate nearest neighbor search for fractal image compression
Fractal image encoding is a computationally intensive method of compression due to its need to find the best match between image sub-blocks by repeatedly searching a large virtual...
Chong Sze Tong, Man Wong