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» Computational complexity of stochastic programming problems
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GPEM
2008
128views more  GPEM 2008»
13 years 11 months ago
Coevolutionary bid-based genetic programming for problem decomposition in classification
In this work a cooperative, bid-based, model for problem decomposition is proposed with application to discrete action domains such as classification. This represents a significan...
Peter Lichodzijewski, Malcolm I. Heywood
VLSID
2007
IEEE
94views VLSI» more  VLSID 2007»
14 years 11 months ago
A Reduced Complexity Algorithm for Minimizing N-Detect Tests
? We give a new recursive rounding linear programming (LP) solution to the problem of N-detect test minimzation. This is a polynomialtime solution that closely approximates the exa...
Kalyana R. Kantipudi, Vishwani D. Agrawal
ICML
2010
IEEE
14 years 1 days 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...
CVPR
2008
IEEE
15 years 1 months ago
Particle filtering for registration of 2D and 3D point sets with stochastic dynamics
In this paper, we propose a particle filtering approach for the problem of registering two point sets that differ by a rigid body transformation. Typically, registration algorithm...
Romeil Sandhu, Samuel Dambreville, Allen Tannenbau...
IWPC
2010
IEEE
13 years 9 months ago
A Simple and Effective Measure for Complex Low-Level Dependencies
The measure dep-degree is a simple indicator for structural problems and complex dependencies on code-level. We model low-level dependencies between program operations as use-def ...
Dirk Beyer, Ashgan Fararooy