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» Self-Randomized Exponentiation Algorithms
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STOC
2004
ACM
102views Algorithms» more  STOC 2004»
16 years 25 days ago
A simple polynomial-time rescaling algorithm for solving linear programs
The perceptron algorithm, developed mainly in the machine learning literature, is a simple greedy method for finding a feasible solution to a linear program (alternatively, for le...
John Dunagan, Santosh Vempala
107
Voted
CAV
2007
Springer
164views Hardware» more  CAV 2007»
15 years 4 months ago
SAT-Based Compositional Verification Using Lazy Learning
Abstract. A recent approach to automated assume-guarantee reasoning (AGR) for concurrent systems relies on computing environment assumptions for components using the L algorithm fo...
Nishant Sinha, Edmund M. Clarke
AAAI
2008
15 years 2 months ago
CRF-OPT: An Efficient High-Quality Conditional Random Field Solver
Conditional random field (CRF) is a popular graphical model for sequence labeling. The flexibility of CRF poses significant computational challenges for training. Using existing o...
Minmin Chen, Yixin Chen, Michael R. Brent
121
Voted
CORR
2012
Springer
195views Education» more  CORR 2012»
13 years 8 months ago
Ranking hubs and authorities using matrix functions
The notions of subgraph centrality and communicability, based on the exponential of the adjacency matrix of the underlying graph, have been effectively used in the analysis of und...
Michele Benzi, Ernesto Estrada, Christine Klymko
AUSSOIS
2001
Springer
15 years 5 months ago
Exact Algorithms for NP-Hard Problems: A Survey
We discuss fast exponential time solutions for NP-complete problems. We survey known results and approaches, we provide pointers to the literature, and we discuss several open prob...
Gerhard J. Woeginger