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COLT
2005
Springer
14 years 1 months ago
Leaving the Span
We discuss a simple sparse linear problem that is hard to learn with any algorithm that uses a linear combination of the training instances as its weight vector. The hardness holds...
Manfred K. Warmuth, S. V. N. Vishwanathan
ICDM
2009
IEEE
149views Data Mining» more  ICDM 2009»
14 years 2 months ago
Accelerated Gradient Method for Multi-task Sparse Learning Problem
—Many real world learning problems can be recast as multi-task learning problems which utilize correlations among different tasks to obtain better generalization performance than...
Xi Chen, Weike Pan, James T. Kwok, Jaime G. Carbon...

Book
778views
15 years 6 months ago
Gaussian Processes for Machine Learning
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
Carl Edward Rasmussen and Christopher K. I. Willia...
CIKM
2008
Springer
13 years 10 months ago
A sparse gaussian processes classification framework for fast tag suggestions
Tagged data is rapidly becoming more available on the World Wide Web. Web sites which populate tagging services offer a good way for Internet users to share their knowledge. An in...
Yang Song, Lu Zhang 0007, C. Lee Giles
ATAL
2009
Springer
14 years 2 months ago
Learning equilibria in repeated congestion games
While the class of congestion games has been thoroughly studied in the multi-agent systems literature, settings with incomplete information have received relatively little attenti...
Moshe Tennenholtz, Aviv Zohar