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» Random sampling and approximation of MAX-CSP problems
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CVPR
2004
IEEE
15 years 11 months ago
Incremental Density Approximation and Kernel-Based Bayesian Filtering for Object Tracking
Statistical density estimation techniques are used in many computer vision applications such as object tracking, background subtraction, motion estimation and segmentation. The pa...
Bohyung Han, Dorin Comaniciu, Ying Zhu, Larry S. D...
ECAI
2004
Springer
15 years 3 months ago
On-Line Search for Solving Markov Decision Processes via Heuristic Sampling
In the past, Markov Decision Processes (MDPs) have become a standard for solving problems of sequential decision under uncertainty. The usual request in this framework is the compu...
Laurent Péret, Frédérick Garc...
68
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FOCS
2002
IEEE
15 years 2 months ago
Rapidly Mixing Markov Chains for Sampling Contingency Tables with a Constant Number of Rows
We consider the problem of sampling almost uniformly from the set of contingency tables with given row and column sums, when the number of rows is a constant. Cryan and Dyer [3] h...
Mary Cryan, Martin E. Dyer, Leslie Ann Goldberg, M...
COCOON
2009
Springer
15 years 4 months ago
On the Diaconis-Gangolli Markov Chain for Sampling Contingency Tables with Cell-Bounded Entries
The problems of uniformly sampling and approximately counting contingency tables have been widely studied, but efficient solutions are only known in special cases. One appealing ap...
Ivona Bezáková, Nayantara Bhatnagar,...
ESA
2010
Springer
246views Algorithms» more  ESA 2010»
14 years 10 months ago
Estimating the Average of a Lipschitz-Continuous Function from One Sample
We study the problem of estimating the average of a Lipschitz continuous function f defined over a metric space, by querying f at only a single point. More specifically, we explore...
Abhimanyu Das, David Kempe