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TIP
2008
133views more  TIP 2008»
13 years 8 months ago
A Recursive Model-Reduction Method for Approximate Inference in Gaussian Markov Random Fields
This paper presents recursive cavity modeling--a principled, tractable approach to approximate, near-optimal inference for large Gauss-Markov random fields. The main idea is to su...
Jason K. Johnson, Alan S. Willsky
IAT
2010
IEEE
13 years 6 months ago
Getting What You Pay For: Is Exploration in Distributed Hill Climbing Really Worth it?
Abstract--The Distributed Stochastic Algorithm (DSA), Distributed Breakout Algorithm (DBA), and variations such as Distributed Simulated Annealing (DSAN), MGM-1, and DisPeL, are di...
Melanie Smith, Roger Mailler
STOC
2001
ACM
111views Algorithms» more  STOC 2001»
14 years 8 months ago
Optimal outlier removal in high-dimensional
We study the problem of finding an outlier-free subset of a set of points (or a probability distribution) in n-dimensional Euclidean space. As in [BFKV 99], a point x is defined t...
John Dunagan, Santosh Vempala
SDM
2010
SIAM
129views Data Mining» more  SDM 2010»
13 years 6 months ago
Cross-Selling Optimization for Customized Promotion
The profit of a retail product not only comes from its own sales, but also comes from its influence on the sales of other products. How to promote the right products to the righ...
Nan Li, Yinghui Yang, Xifeng Yan
ICDE
2006
IEEE
201views Database» more  ICDE 2006»
14 years 9 months ago
Approximate Data Collection in Sensor Networks using Probabilistic Models
Wireless sensor networks are proving to be useful in a variety of settings. A core challenge in these networks is to minimize energy consumption. Prior database research has propo...
David Chu, Amol Deshpande, Joseph M. Hellerstein, ...