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APPROX
2005
Springer
111views Algorithms» more  APPROX 2005»
15 years 4 months ago
Sampling Bounds for Stochastic Optimization
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
Moses Charikar, Chandra Chekuri, Martin Pál
DAC
1994
ACM
15 years 2 months ago
Optimum Functional Decomposition Using Encoding
In this paper, we revisit the classical problem of functional decomposition [1, 2] that arises so often in logic synthesis. One basic problem that has remained largely unaddressed...
Rajeev Murgai, Robert K. Brayton, Alberto L. Sangi...
NIPS
2004
15 years 10 days ago
Exponentiated Gradient Algorithms for Large-margin Structured Classification
We consider the problem of structured classification, where the task is to predict a label y from an input x, and y has meaningful internal structure. Our framework includes super...
Peter L. Bartlett, Michael Collins, Benjamin Taska...
ICML
2010
IEEE
15 years 1 days ago
Boosting Classifiers with Tightened L0-Relaxation Penalties
We propose a novel boosting algorithm which improves on current algorithms for weighted voting classification by striking a better balance between classification accuracy and the ...
Noam Goldberg, Jonathan Eckstein
GECCO
2009
Springer
163views Optimization» more  GECCO 2009»
15 years 5 months ago
Dealing with inheritance in OO evolutionary testing
Most of the software developed in the world follows the object-oriented (OO) paradigm. However, the existing work on evolutionary testing is mainly targeted to procedural language...
Javier Ferrer, J. Francisco Chicano, Enrique Alba