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JCC
2008
131views more  JCC 2008»
14 years 10 months ago
An optimized initialization algorithm to ensure accuracy in quantum Monte Carlo calculations
: Quantum Monte Carlo (QMC) calculations require the generation of random electronic configurations with respect to a desired probability density, usually the square of the magnitu...
Daniel R. Fisher, David R. Kent IV, Michael T. Fel...
66
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JMLR
2010
88views more  JMLR 2010»
14 years 5 months ago
Inference and Learning in Networks of Queues
Probabilistic models of the performance of computer systems are useful both for predicting system performance in new conditions, and for diagnosing past performance problems. The ...
Charles A. Sutton, Michael I. Jordan
ECCV
2004
Springer
16 years 16 days ago
An MCMC-Based Particle Filter for Tracking Multiple Interacting Targets
Abstract. We describe a Markov chain Monte Carlo based particle filter that effectively deals with interacting targets, i.e., targets that are influenced by the proximity and/or be...
Zia Khan, Tucker R. Balch, Frank Dellaert
SIGMOD
2011
ACM
250views Database» more  SIGMOD 2011»
14 years 1 months ago
Hybrid in-database inference for declarative information extraction
In the database community, work on information extraction (IE) has centered on two themes: how to effectively manage IE tasks, and how to manage the uncertainties that arise in th...
Daisy Zhe Wang, Michael J. Franklin, Minos N. Garo...
ICCV
2011
IEEE
13 years 10 months ago
Perturb-and-MAP Random Fields: Using Discrete Optimization\\to Learn and Sample from Energy Models
We propose a novel way to induce a random field from an energy function on discrete labels. It amounts to locally injecting noise to the energy potentials, followed by finding t...
George Papandreou, Alan L. Yuille