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» On the Advantage over Random for Maximum Acyclic Subgraph
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ICML
2001
IEEE
14 years 8 months ago
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hid...
John D. Lafferty, Andrew McCallum, Fernando C. N. ...
JMLR
2008
150views more  JMLR 2008»
13 years 7 months ago
Discriminative Learning of Max-Sum Classifiers
The max-sum classifier predicts n-tuple of labels from n-tuple of observable variables by maximizing a sum of quality functions defined over neighbouring pairs of labels and obser...
Vojtech Franc, Bogdan Savchynskyy
ESA
2004
Springer
129views Algorithms» more  ESA 2004»
14 years 1 months ago
Contraction and Treewidth Lower Bounds
Edge contraction is shown to be a useful mechanism to improve lower bound heuristics for treewidth. A successful lower bound for treewidth is the degeneracy: the maximum over all ...
Hans L. Bodlaender, Arie M. C. A. Koster, Thomas W...
ASPDAC
2007
ACM
112views Hardware» more  ASPDAC 2007»
13 years 11 months ago
Efficient Second-Order Iterative Methods for IR Drop Analysis in Power Grid
Due to the extremely large sizes of power grids, IR drop analysis has become a computationally challenging problem both in terms of runtime and memory usage. It has been shown in [...
Yu Zhong, Martin D. F. Wong
SODA
2012
ACM
217views Algorithms» more  SODA 2012»
11 years 10 months ago
Polynomial integrality gaps for strong SDP relaxations of Densest k-subgraph
The Densest k-subgraph problem (i.e. find a size k subgraph with maximum number of edges), is one of the notorious problems in approximation algorithms. There is a significant g...
Aditya Bhaskara, Moses Charikar, Aravindan Vijayar...