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108
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APPROX
2005
Springer
111views Algorithms» more  APPROX 2005»
15 years 6 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 4 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...
99
Voted
NIPS
2004
15 years 1 months 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...
110
Voted
ICML
2010
IEEE
15 years 1 months 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 7 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