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ACML
2009
Springer
14 years 24 days ago
Max-margin Multiple-Instance Learning via Semidefinite Programming
In this paper, we present a novel semidefinite programming approach for multiple-instance learning. We first formulate the multipleinstance learning as a combinatorial maximum marg...
Yuhong Guo
PPDP
2010
Springer
13 years 7 months ago
A declarative approach to robust weighted Max-SAT
The presence of uncertainty in the real world makes robustness to be a desired property of solutions to constraint satisfaction problems. Roughly speaking, a solution is robust if...
Miquel Bofill, Dídac Busquets, Mateu Villar...
SSIAI
2000
IEEE
14 years 1 months ago
A New Bayesian Relaxation Framework for the Estimation and Segmentation of Multiple Motions
In this paper we propose a new probabilistic relaxation framework to perform robust multiple motion estimation and segmentation from a sequence of images. Our approach uses displa...
Alexander Strehl, Jake K. Aggarwal
AIPS
2007
13 years 11 months ago
Robust Local Search and Its Application to Generating Robust Schedules
In this paper, we propose an extended local search framework to solve combinatorial optimization problems with data uncertainty. Our approach represents a major departure from sce...
Hoong Chuin Lau, Thomas Ou, Fei Xiao
ICTAI
1999
IEEE
14 years 1 months ago
Search Strategies for Hybrid Search Spaces
Recently, there has been much interest in enhancing purely combinatorial formalisms with numerical information. For example, planning formalisms can be enriched by taking resource...
Carla P. Gomes, Bart Selman