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 8 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...