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» Logic programming for combinatorial problems
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FOCS
2005
IEEE
15 years 8 months ago
Sampling-based Approximation Algorithms for Multi-stage Stochastic
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
DAGSTUHL
2007
15 years 4 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
135
Voted
TLDI
2009
ACM
169views Formal Methods» more  TLDI 2009»
15 years 11 months ago
Relational parametricity for references and recursive types
We present a possible world semantics for a call-by-value higherorder programming language with impredicative polymorphism, general references, and recursive types. The model is o...
Lars Birkedal, Kristian Støvring, Jacob Tha...
FOCS
2002
IEEE
15 years 7 months ago
Low-Dimensional Linear Programming with Violations
Two decades ago, Megiddo and Dyer showed that linear programming in two and three dimensions (and subsequently any constant number of dimensions) can be solved in linear time. In ...
Timothy M. Chan
KBSE
1998
IEEE
15 years 6 months ago
Automated Software Test Data Generation for Complex Programs
We report on GADGET, a new software test generation system that uses combinatorial optimization to obtain condition/decision coverage of C/C++ programs. The GADGET system is fully...
Christoph C. Michael, Gary McGraw