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» Complexity of Inference in Graphical Models
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JMLR
2012
13 years 5 months ago
Adaptive MCMC with Bayesian Optimization
This paper proposes a new randomized strategy for adaptive MCMC using Bayesian optimization. This approach applies to nondifferentiable objective functions and trades off explor...
Nimalan Mahendran, Ziyu Wang, Firas Hamze, Nando d...
AAAI
2007
15 years 4 months ago
On the Prospects for Building a Working Model of the Visual Cortex
Human visual capability has remained largely beyond the reach of engineered systems despite intensive study and considerable progress in problem understanding, algorithms and comp...
Thomas Dean, Glenn Carroll, Richard Washington
ACL
2007
15 years 3 months ago
Constituent Parsing with Incremental Sigmoid Belief Networks
We introduce a framework for syntactic parsing with latent variables based on a form of dynamic Sigmoid Belief Networks called Incremental Sigmoid Belief Networks. We demonstrate ...
Ivan Titov, James Henderson
CVPR
2009
IEEE
15 years 9 months ago
Robust shadow and illumination estimation using a mixture model
Illuminant estimation from shadows typically relies on accurate segmentation of the shadows and knowledge of exact 3D geometry, while shadow estimation is difficult in the presen...
Alexandros Panagopoulos, Dimitris Samaras, Nikos P...
CVPR
2006
IEEE
16 years 4 months ago
Composite Templates for Cloth Modeling and Sketching
Cloth modeling and recognition is an important and challenging problem in both vision and graphics tasks, such as dressed human recognition and tracking, human sketch and portrait...
Hong Chen, Zijian Xu, Ziqiang Liu, Song Chun Zhu