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AMAI
2004
Springer
15 years 4 months ago
Approximate Probabilistic Constraints and Risk-Sensitive Optimization Criteria in Markov Decision Processes
The majority of the work in the area of Markov decision processes has focused on expected values of rewards in the objective function and expected costs in the constraints. Althou...
Dmitri A. Dolgov, Edmund H. Durfee
STOC
1991
ACM
84views Algorithms» more  STOC 1991»
15 years 2 months ago
Self-Testing/Correcting for Polynomials and for Approximate Functions
The study of self-testing/correcting programs was introduced in [8] in order to allow one to use program P to compute function f without trusting that P works correctly. A self-te...
Peter Gemmell, Richard J. Lipton, Ronitt Rubinfeld...
ICDM
2009
IEEE
117views Data Mining» more  ICDM 2009»
15 years 5 months ago
Clustering with Multiple Graphs
—In graph-based learning models, entities are often represented as vertices in an undirected graph with weighted edges describing the relationships between entities. In many real...
Wei Tang, Zhengdong Lu, Inderjit S. Dhillon
AAAI
2004
15 years 18 days ago
PROBCONS: Probabilistic Consistency-Based Multiple Alignment of Amino Acid Sequences
Obtaining an accurate multiple alignment of protein sequences is a difficult computational problem for which many heuristic techniques sacrifice optimality to achieve reasonable r...
Chuong B. Do, Michael Brudno, Serafim Batzoglou
CVPR
2008
IEEE
16 years 1 months ago
Shape prior segmentation of multiple objects with graph cuts
We present a new shape prior segmentation method using graph cuts capable of segmenting multiple objects. The shape prior energy is based on a shape distance popular with level se...
Nhat Vu, B. S. Manjunath