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2005
Tsinghua U.
16 years 11 days ago
What is worth learning from parallel workloads?: a user and session based analysis
Learning useful and predictable features from past workloads and exploiting them well is a major source of improvement in many operating system problems. We review known parallel ...
Julia Zilber, Ofer Amit, David Talby
EOR
2007
165views more  EOR 2007»
15 years 6 months ago
Adaptive credit scoring with kernel learning methods
Credit scoring is a method of modelling potential risk of credit applications. Traditionally, logistic regression, linear regression and discriminant analysis are the most popular...
Yingxu Yang
ICDAR
2007
IEEE
16 years 1 months ago
Energy-Based Models in Document Recognition and Computer Vision
The Machine Learning and Pattern Recognition communities are facing two challenges: solving the normalization problem, and solving the deep learning problem. The normalization pro...
Yann LeCun, Sumit Chopra, Marc'Aurelio Ranzato, Fu...
TCSV
2008
195views more  TCSV 2008»
15 years 6 months ago
Locality Versus Globality: Query-Driven Localized Linear Models for Facial Image Computing
Conventional subspace learning or recent feature extraction methods consider globality as the key criterion to design discriminative algorithms for image classification. We demonst...
Yun Fu, Zhu Li, Junsong Yuan, Ying Wu, Thomas S. H...
COGSCI
2008
139views more  COGSCI 2008»
15 years 7 months ago
A Computational Model of Early Argument Structure Acquisition
How children go about learning the general regularities that govern language, as well as keeping track of the exceptions to them, remains one of the challenging open questions in ...
Afra Alishahi, Suzanne Stevenson