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» Approximate Inference and Constrained Optimization
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CVPR
2003
IEEE
14 years 9 months ago
An Efficient Approach to Learning Inhomogeneous Gibbs Model
Inhomogeneous Gibbs model (IGM) [4] is an effective maximum entropy model in characterizing complex highdimensional distributions. However, its training process is so slow that th...
Ziqiang Liu, Hong Chen, Heung-Yeung Shum
INFOCOM
2002
IEEE
14 years 16 days ago
Downlink Power Allocation for Multi-class CDMA Wireless Networks
Abstract—In this paper we consider the downlink power allocation problem for multi-class CDMA wireless networks. We use a utility based power allocation framework to treat multi-...
Jangwon Lee, Ravi Mazumdar, Ness B. Shroff
ICML
2010
IEEE
13 years 8 months ago
Submodular Dictionary Selection for Sparse Representation
We develop an efficient learning framework to construct signal dictionaries for sparse representation by selecting the dictionary columns from multiple candidate bases. By sparse,...
Andreas Krause, Volkan Cevher
ICCV
2003
IEEE
14 years 9 months ago
Ranking Prior Likelihood Distributions for Bayesian Shape Localization Framework
In this paper, we formulate the shape localization problem in the Bayesian framework. In the learning stage, we propose the Constrained RankBoost approach to model the likelihood ...
Shuicheng Yan, Mingjing Li, HongJiang Zhang, QianS...
CVPR
2012
IEEE
11 years 10 months ago
Unsupervised learning of translation invariant occlusive components
We study unsupervised learning of occluding objects in images of visual scenes. The derived learning algorithm is based on a probabilistic generative model which parameterizes obj...
Zhenwen Dai, Jörg Lücke