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» Approximate Inference and Constrained Optimization
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CISS
2008
IEEE
14 years 2 months ago
Subgradient methods in network resource allocation: Rate analysis
— We consider dual subgradient methods for solving (nonsmooth) convex constrained optimization problems. Our focus is on generating approximate primal solutions with performance ...
Angelia Nedic, Asuman E. Ozdaglar
KDD
2010
ACM
188views Data Mining» more  KDD 2010»
13 years 9 months ago
Inferring networks of diffusion and influence
Information diffusion and virus propagation are fundamental processes talking place in networks. While it is often possible to directly observe when nodes become infected, observi...
Manuel Gomez-Rodriguez, Jure Leskovec, Andreas Kra...
IJCAI
1997
13 years 9 months ago
Mini-Buckets: A General Scheme for Generating Approximations in Automated Reasoning
The class of algorithms for approximating reasoning tasks presented in this paper is based on approximating the general bucket elimination framework. The algorithms have adjustabl...
Rina Dechter
ACCV
2006
Springer
14 years 1 months ago
Online Updating Appearance Generative Mixture Model for Meanshift Tracking
This paper proposes an appearance generative mixture model based on key frames for meanshift tracking. Meanshift tracking algorithm tracks object by maximizing the similarity betwe...
Jilin Tu, Hai Tao, Thomas S. Huang
JMLR
2010
137views more  JMLR 2010»
13 years 2 months ago
Importance Sampling for Continuous Time Bayesian Networks
A continuous time Bayesian network (CTBN) uses a structured representation to describe a dynamic system with a finite number of states which evolves in continuous time. Exact infe...
Yu Fan, Jing Xu, Christian R. Shelton