SIAMJO
2010
13 years 6 months ago
2010
We study the problem of minimizing the expected loss of a linear predictor while constraining its sparsity, i.e., bounding the number of features used by the predictor. While the r...
ICML
2010
IEEE
14 years 15 days ago
2010
IEEE
We describe and analyze efficient algorithms for learning a linear predictor from examples when the learner can only view a few attributes of each training example. This is the ca...
ICASSP
2009
IEEE
14 years 3 months ago
2009
IEEE
In low bit-rate coders, the near-sample and far-sample redundancies of the speech signal are usually removed by a cascade of a shortterm and a long-term linear predictor. These tw...