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» On the Convergence of Bound Optimization Algorithms
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ML
2008
ACM
15 years 6 months ago
Large margin vs. large volume in transductive learning
Abstract. We consider a large volume principle for transductive learning that prioritizes the transductive equivalence classes according to the volume they occupy in hypothesis spa...
Ran El-Yaniv, Dmitry Pechyony, Vladimir Vapnik
CEC
2008
IEEE
16 years 1 months ago
A study on constrained MA using GA and SQP: Analytical vs. finite-difference gradients
— Many deterministic algorithms in the context of constrained optimization require the first-order derivatives, or the gradient vectors, of the objective and constraint function...
Stephanus Daniel Handoko, Chee Keong Kwoh, Yew-Soo...
INFOCOM
2007
IEEE
16 years 29 days ago
Measurement-Based Self Organization of Interfering 802.11 Wireless Access Networks
— The popularity of IEEE 802.11 WLANs has led to dense deployments in urban areas. High density leads to suboptimal performance unless the interfering networks learn how to optim...
Bruno Kauffmann, François Baccelli, Augusti...
JMLR
2012
13 years 9 months ago
Online Incremental Feature Learning with Denoising Autoencoders
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, ...
Guanyu Zhou, Kihyuk Sohn, Honglak Lee
SAC
2009
ACM
16 years 1 months ago
A gradient oriented recombination scheme for evolution strategies
This paper proposes a novel recombination scheme for evolutionary algorithms, which can guide the new population generation towards the maximum increase of the objective function....
Haifeng Chen, Guofei Jiang