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JMLR
2008
230views more  JMLR 2008»
15 years 6 months ago
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
TSMC
2008
164views more  TSMC 2008»
15 years 6 months ago
Bagging and Boosting Negatively Correlated Neural Networks
In this paper, we propose two cooperative ensemble learning algorithms, i.e., NegBagg and NegBoost, for designing neural network (NN) ensembles. The proposed algorithms incremental...
Md. Monirul Islam, Xin Yao, S. M. Shahriar Nirjon,...
ICDCS
2012
IEEE
13 years 9 months ago
Securing Virtual Coordinates by Enforcing Physical Laws
—Virtual coordinate systems (VCS) provide accurate estimations of latency between arbitrary hosts on a network, while conducting a small amount of actual measurements and relying...
Jeffrey Seibert, Sheila Becker, Cristina Nita-Rota...
AAAI
2012
13 years 9 months ago
Online Kernel Selection: Algorithms and Evaluations
Kernel methods have been successfully applied to many machine learning problems. Nevertheless, since the performance of kernel methods depends heavily on the type of kernels being...
Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Y...
AVBPA
2003
Springer
133views Biometrics» more  AVBPA 2003»
15 years 10 months ago
LUT-Based Adaboost for Gender Classification
There are two main approaches to the problem of gender classification, Support Vector Machines (SVMs) and Adaboost learning methods, of which SVMs are better in correct rate but ar...
Bo Wu, Haizhou Ai, Chang Huang
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