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» Superset Learning Based on Generalized Loss Minimization
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CSFW
2011
IEEE
13 years 9 months ago
Regret Minimizing Audits: A Learning-Theoretic Basis for Privacy Protection
Abstract—Audit mechanisms are essential for privacy protection in permissive access control regimes, such as in hospitals where denying legitimate access requests can adversely a...
Jeremiah Blocki, Nicolas Christin, Anupam Datta, A...
SIAMJO
2010
125views more  SIAMJO 2010»
14 years 4 months ago
Trading Accuracy for Sparsity in Optimization Problems with Sparsity Constraints
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...
Shai Shalev-Shwartz, Nathan Srebro, Tong Zhang
ICML
2006
IEEE
15 years 10 months ago
Cost-sensitive learning with conditional Markov networks
There has been a recent, growing interest in classification and link prediction in structured domains. Methods such as conditional random fields and relational Markov networks sup...
Prithviraj Sen, Lise Getoor
INFOCOM
2008
IEEE
15 years 4 months ago
Queueing Analysis of Loss Systems with Variable Optical Delay Lines
—Recently, a new optical device called variable optical delay line (VODL) has been proposed in the literature. As suggested by its name, the delay of a VODL can be dynamically se...
Duan-Shin Lee, Cheng-Shang Chang, Jay Cheng, Horng...
CORR
2012
Springer
232views Education» more  CORR 2012»
13 years 5 months ago
Smoothing Proximal Gradient Method for General Structured Sparse Learning
We study the problem of learning high dimensional regression models regularized by a structured-sparsity-inducing penalty that encodes prior structural information on either input...
Xi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbone...