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JMLR
2011
192views more  JMLR 2011»
14 years 4 months ago
Minimum Description Length Penalization for Group and Multi-Task Sparse Learning
We propose a framework MIC (Multiple Inclusion Criterion) for learning sparse models based on the information theoretic Minimum Description Length (MDL) principle. MIC provides an...
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Unga...
ATAL
2007
Springer
15 years 3 months ago
Sharing experiences to learn user characteristics in dynamic environments with sparse data
This paper investigates the problem of estimating the value of probabilistic parameters needed for decision making in environments in which an agent, operating within a multi-agen...
David Sarne, Barbara J. Grosz
SODA
2008
ACM
184views Algorithms» more  SODA 2008»
14 years 11 months ago
Coresets, sparse greedy approximation, and the Frank-Wolfe algorithm
The problem of maximizing a concave function f(x) in a simplex S can be solved approximately by a simple greedy algorithm. For given k, the algorithm can find a point x(k) on a k-...
Kenneth L. Clarkson
AAAI
2011
13 years 9 months ago
Sparse Matrix-Variate t Process Blockmodels
We consider the problem of modeling network interactions and identifying latent groups of network nodes. This problem is challenging due to the facts i) that the network nodes are...
Zenglin Xu, Feng Yan, Yuan Qi
ESANN
2004
14 years 11 months ago
Sparse LS-SVMs using additive regularization with a penalized validation criterion
This paper is based on a new way for determining the regularization trade-off in least squares support vector machines (LS-SVMs) via a mechanism of additive regularization which ha...
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De ...