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KDD
2010
ACM
274views Data Mining» more  KDD 2010»
13 years 11 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing
ICCV
2009
IEEE
1069views Computer Vision» more  ICCV 2009»
15 years 17 days ago
An efficient algorithm for Co-segmentation
This paper is focused on the Co-segmentation problem [1] – where the objective is to segment a similar object from a pair of images. The background in the two images may be ar...
Dorit S. Hochbaum, Vikas Singh
ICIP
2008
IEEE
14 years 2 months ago
MAP-MRF approach for binarization of degraded document image
We propose an algorithm for the binarization of document images degraded by uneven light distribution, based on the Markov Random Field modeling with Maximum A Posteriori probabil...
Jung Gap Kuk, Nam Ik Cho, Kyoung Mu Lee
CDC
2010
IEEE
102views Control Systems» more  CDC 2010»
13 years 2 months ago
Stock market trading via stochastic network optimization
We consider the problem of dynamic buying and selling of shares from a collection of N stocks with random price fluctuations. To limit investment risk, we place an upper bound on t...
Michael J. Neely
KI
2006
Springer
13 years 7 months ago
A Framework for Quasi-exact Optimization Using Relaxed Best-First Search
Abstract. In this paper, a framework for previous and new quasi-exact extensions of the A -algorithm is presented. In contrast to previous approaches, the new methods guarantee to ...
Rüdiger Ebendt, Rolf Drechsler