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CORR
2010
Springer
70views Education» more  CORR 2010»
15 years 6 months ago
Structured sparsity-inducing norms through submodular functions
Sparse methods for supervised learning aim at finding good linear predictors from as few variables as possible, i.e., with small cardinality of their supports. This combinatorial ...
Francis Bach
NAACL
2010
15 years 4 months ago
Softmax-Margin CRFs: Training Log-Linear Models with Cost Functions
We describe a method of incorporating taskspecific cost functions into standard conditional log-likelihood (CLL) training of linear structured prediction models. Recently introduc...
Kevin Gimpel, Noah A. Smith
STOC
2012
ACM
209views Algorithms» more  STOC 2012»
13 years 9 months ago
Nearly optimal solutions for the chow parameters problem and low-weight approximation of halfspaces
The Chow parameters of a Boolean function f : {−1, 1}n → {−1, 1} are its n + 1 degree-0 and degree-1 Fourier coefficients. It has been known since 1961 [Cho61, Tan61] that ...
Anindya De, Ilias Diakonikolas, Vitaly Feldman, Ro...
MCS
2005
Springer
15 years 12 months ago
Between Two Extremes: Examining Decompositions of the Ensemble Objective Function
We study how the error of an ensemble regression estimator can be decomposed into two components: one accounting for the individual errors and the other accounting for the correlat...
Gavin Brown, Jeremy L. Wyatt, Ping Sun
VLSID
2010
IEEE
155views VLSI» more  VLSID 2010»
15 years 10 months ago
Digital Microfluidic Biochips: A Vision for Functional Diversity and More than Moore
Abstract—Microfluidics-based biochips are revolutionizing highthroughput sequencing, parallel immunoassays, clinical diagnostics, and drug discovery. These devices enable the pre...
Krishnendu Chakrabarty