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AAAI
2011
12 years 9 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
FAW
2008
Springer
127views Algorithms» more  FAW 2008»
13 years 10 months ago
Visiting a Polygon on the Optimal Way to a Query Point
Abstract. We study a constrained version of the shortest path problem in polygonal domains, in which the path must visit a given target polygon. We provide an efficient algorithm f...
Ramtin Khosravi, Mohammad Ghodsi
BMCBI
2011
13 years 4 months ago
Implementation of Force Distribution Analysis for Molecular Dynamics simulations
Background: The way mechanical stress is distributed inside and propagated by proteins and other biopolymers largely defines their function. Yet, determining the network of intera...
Wolfram Stacklies, Christian Seifert, Frauke Graet...
CVPR
2009
IEEE
14 years 7 months ago
Markov Chain Monte Carlo Combined with Deterministic Methods for Markov Random Field Optimization
Many vision problems have been formulated as en- ergy minimization problems and there have been signif- icant advances in energy minimization algorithms. The most widely-used energ...
Wonsik Kim (Seoul National University), Kyoung Mu ...
SC
1995
ACM
14 years 18 days ago
Parallel Matrix-Vector Product Using Approximate Hierarchical Methods
Matrix-vector products (mat-vecs) form the core of iterative methods used for solving dense linear systems. Often, these systems arise in the solution of integral equations used i...
Ananth Grama, Vipin Kumar, Ahmed H. Sameh