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» Linear logical approximations
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ICML
2010
IEEE
13 years 11 months ago
Learning Efficiently with Approximate Inference via Dual Losses
Many structured prediction tasks involve complex models where inference is computationally intractable, but where it can be well approximated using a linear programming relaxation...
Ofer Meshi, David Sontag, Tommi Jaakkola, Amir Glo...
EOR
2008
93views more  EOR 2008»
13 years 10 months ago
Approximate methods for convex minimization problems with series-parallel structure
Consider a problem of minimizing a separable, strictly convex, monotone and differentiable function on a convex polyhedron generated by a system of m linear inequalities. The probl...
Adi Ben-Israel, Genrikh Levin, Yuri Levin, Boris R...
TLDI
2003
ACM
14 years 3 months ago
The logical approach to stack typing
We develop a logic for reasoning about adjacency and separation of memory blocks, as well as aliasing of pointers. We provide a memory model for our logic and present a sound set ...
Amal J. Ahmed, David Walker
CORR
2011
Springer
143views Education» more  CORR 2011»
13 years 1 months ago
Probabilistic Logic: Many-valuedness and Intensionality
The probability theory is a well-studied branch of mathematics, in order to carry out formal reasoning about probability. Thus, it is important to have a logic, both for computati...
Zoran Majkic
ICLP
2010
Springer
14 years 1 months ago
Improving the Efficiency of Gibbs Sampling for Probabilistic Logical Models by Means of Program Specialization
Abstract. There is currently a large interest in probabilistic logical models. A popular algorithm for approximate probabilistic inference with such models is Gibbs sampling. From ...
Daan Fierens