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» A Markov Chain Monte Carlo Approach to Stereovision
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CVPR
1999
IEEE
13 years 11 months ago
A New Bayesian Framework for Object Recognition
We introduce an approach to feature-based object recognition, using maximum a posteriori (MAP) estimation under a Markov random field (MRF) model. This approach provides an effici...
Yuri Boykov, Daniel P. Huttenlocher
NIPS
2001
13 years 8 months ago
Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning
Policy gradient methods for reinforcement learning avoid some of the undesirable properties of the value function approaches, such as policy degradation (Baxter and Bartlett, 2001...
Evan Greensmith, Peter L. Bartlett, Jonathan Baxte...
ECCV
2002
Springer
14 years 9 months ago
Hyperdynamics Importance Sampling
Sequential random sampling (`Markov Chain Monte-Carlo') is a popular strategy for many vision problems involving multimodal distributions over high-dimensional parameter spac...
Cristian Sminchisescu, Bill Triggs
WWW
2008
ACM
14 years 8 months ago
Analyzing search engine advertising: firm behavior and cross-selling in electronic markets
The phenomenon of sponsored search advertising is gaining ground as the largest source of revenues for search engines. Firms across different industries have are beginning to adop...
Anindya Ghose, Sha Yang
CVPR
2010
IEEE
1208views Computer Vision» more  CVPR 2010»
14 years 3 months ago
Visual Tracking Decomposition
We propose a novel tracking algorithm that can work robustly in a challenging scenario such that several kinds of appearance and motion changes of an object occur at the same time....
Junseok Kwon (Seoul National University), Kyoung M...