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» The Inference Problem: A Survey
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AAAI
2011
12 years 10 months ago
Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models
Coarse-to-fine approaches use sequences of increasingly fine approximations to control the complexity of inference and learning. These techniques are often used in NLP and visio...
Chloe Kiddon, Pedro Domingos
KER
2008
107views more  KER 2008»
13 years 10 months ago
Tuplespace-based computing for the Semantic Web: a survey of the state-of-the-art
Semantic technologies promise to solve many challenging problems of the present Web applications. As they achieve a feasible level of maturity, they become increasingly accepted i...
Lyndon J. B. Nixon, Elena Paslaru Bontas Simperl, ...
ORL
1998
116views more  ORL 1998»
13 years 9 months ago
Heuristic solution of the multisource Weber problem as a p-median problem
Good heuristic solutions for large Multisource Weber problems can be obtained by solving related p-median problems in which potential locations of the facilities are users location...
Pierre Hansen, Nenad Mladenovic, Éric D. Ta...
COLT
1999
Springer
14 years 2 months ago
Regret Bounds for Prediction Problems
We present a unified framework for reasoning about worst-case regret bounds for learning algorithms. This framework is based on the theory of duality of convex functions. It brin...
Geoffrey J. Gordon
CPAIOR
2008
Springer
13 years 11 months ago
The Accuracy of Search Heuristics: An Empirical Study on Knapsack Problems
Theoretical models for the evaluation of quickly improving search strategies, like limited discrepancy search, are based on specific assumptions regarding the probability that a va...
Daniel H. Leventhal, Meinolf Sellmann