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IJCV
2000
86views more  IJCV 2000»
14 years 11 months ago
Statistical Learning Theory: A Primer
In this paper we first overview the main concepts of Statistical Learning Theory, a framework in which learning from examples can be studied in a principled way. We then briefly di...
Theodoros Evgeniou, Massimiliano Pontil, Tomaso Po...
NN
2010
Springer
189views Neural Networks» more  NN 2010»
14 years 6 months ago
Sparse kernel learning with LASSO and Bayesian inference algorithm
Kernelized LASSO (Least Absolute Selection and Shrinkage Operator) has been investigated in two separate recent papers (Gao et al., 2008) and (Wang et al., 2007). This paper is co...
Junbin Gao, Paul W. Kwan, Daming Shi
ALT
2006
Springer
15 years 8 months ago
Unsupervised Slow Subspace-Learning from Stationary Processes
Abstract. We propose a method of unsupervised learning from stationary, vector-valued processes. A low-dimensional subspace is selected on the basis of a criterion which rewards da...
Andreas Maurer
IJCNN
2007
IEEE
15 years 6 months ago
Random Feature Subset Selection for Analysis of Data with Missing Features
Abstract - We discuss an ensemble-of-classifiers based algorithm for the missing feature problem. The proposed approach is inspired in part by the random subspace method, and in pa...
Joseph DePasquale, Robi Polikar
COMCOM
2010
118views more  COMCOM 2010»
14 years 9 months ago
Mini-slot scheduling for IEEE 802.16d chain and grid mesh networks
This work considers the mini-slot scheduling problem in IEEE 802.16d wireless mesh networks (WMNs). An efficient mini-slot scheduling needs to take into account the transmission o...
Jia-Ming Liang, Ho-Cheng Wu, Jen-Jee Chen, Yu-Chee...