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DAGSTUHL
2007
15 years 6 months ago
Sampling-based Approximation Algorithms for Multi-stage Stochastic Optimization
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
Chaitanya Swamy, David B. Shmoys
132
Voted
DLT
2003
15 years 6 months ago
NFA Reduction Algorithms by Means of Regular Inequalities
We present different techniques for reducing the number of states and transitions in nondeterministic automata. These techniques are based on the two preorders over the set of st...
Jean-Marc Champarnaud, Fabien Coulon
CORR
2008
Springer
89views Education» more  CORR 2008»
15 years 4 months ago
Flow Faster: Efficient Decision Algorithms for Probabilistic Simulations
Strong and weak simulation relations have been proposed for Markov chains, while strong simulation and strong probabilistic simulation relations have been proposed for probabilisti...
Lijun Zhang, Holger Hermanns, Friedrich Eisenbrand...
142
Voted
CORR
2008
Springer
108views Education» more  CORR 2008»
15 years 4 months ago
Resolution Trees with Lemmas: Resolution Refinements that Characterize DLL Algorithms with Clause Learning
Resolution refinements called w-resolution trees with lemmas (WRTL) and with input lemmas (WRTI) are introduced. Dag-like resolution is equivalent to both WRTL and WRTI when there...
Samuel R. Buss, Jan Hoffmann 0002, Jan Johannsen
169
Voted
ALGORITHMICA
1998
184views more  ALGORITHMICA 1998»
15 years 4 months ago
Approximation Algorithms for Connected Dominating Sets
The dominatingset problemin graphs asks for a minimumsize subset of vertices with the followingproperty: each vertex is required to either be in the dominating set, or adjacent to...
Sudipto Guha, Samir Khuller