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» A Sampling Method Focusing on Practicality
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AAAI
2007
13 years 11 months ago
Stochastic Optimization for Collision Selection in High Energy Physics
Artificial intelligence has begun to play a critical role in basic science research. In high energy physics, AI methods can aid precision measurements that elucidate the underlyi...
Shimon Whiteson, Daniel Whiteson
SDM
2010
SIAM
195views Data Mining» more  SDM 2010»
13 years 10 months ago
MACH: Fast Randomized Tensor Decompositions
Tensors naturally model many real world processes which generate multi-aspect data. Such processes appear in many different research disciplines, e.g, chemometrics, computer visio...
Charalampos E. Tsourakakis
SODA
2004
ACM
124views Algorithms» more  SODA 2004»
13 years 10 months ago
On contract-and-refine transformations between phylogenetic trees
The inference of evolutionary trees using approaches which attempt to solve the maximum parsimony (MP) and maximum likelihood (ML) optimization problems is a standard part of much...
Ganeshkumar Ganapathy, Vijaya Ramachandran, Tandy ...
CGF
2008
129views more  CGF 2008»
13 years 8 months ago
Sequential Monte Carlo Adaptation in Low-Anisotropy Participating Media
This paper presents a novel method that effectively combines both control variates and importance sampling in a sequential Monte Carlo context. The radiance estimates computed dur...
Vincent Pegoraro, Ingo Wald, Steven G. Parker
KDD
2005
ACM
103views Data Mining» more  KDD 2005»
14 years 9 months ago
Fast discovery of unexpected patterns in data, relative to a Bayesian network
We consider a model in which background knowledge on a given domain of interest is available in terms of a Bayesian network, in addition to a large database. The mining problem is...
Szymon Jaroszewicz, Tobias Scheffer