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JMLR
2010
103views more  JMLR 2010»
13 years 4 months ago
Learning Nonlinear Dynamic Models from Non-sequenced Data
Virtually all methods of learning dynamic systems from data start from the same basic assumption: the learning algorithm will be given a sequence of data generated from the dynami...
Tzu-Kuo Huang, Le Song, Jeff Schneider
ICASSP
2008
IEEE
14 years 4 months ago
Sparse reconstruction by separable approximation
Finding sparse approximate solutions to large underdetermined linear systems of equations is a common problem in signal/image processing and statistics. Basis pursuit, the least a...
Stephen J. Wright, Robert D. Nowak, Mário A...
KDD
2010
ACM
245views Data Mining» more  KDD 2010»
13 years 12 months ago
Learning incoherent sparse and low-rank patterns from multiple tasks
We consider the problem of learning incoherent sparse and lowrank patterns from multiple tasks. Our approach is based on a linear multi-task learning formulation, in which the spa...
Jianhui Chen, Ji Liu, Jieping Ye
TIT
1998
112views more  TIT 1998»
13 years 9 months ago
Application of Network Calculus to Guaranteed Service Networks
—We use recent network calculus results to study some properties of lossless multiplexing as it may be used in guaranteed service networks. We call network calculus a set of resu...
Jean-Yves Le Boudec
CSDA
2006
109views more  CSDA 2006»
13 years 10 months ago
Possibility theory and statistical reasoning
Numerical possibility distributions can encode special convex families of probability measures. The connection between possibility theory and probability theory is potentially fru...
Didier Dubois