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ICML
2009
IEEE
16 years 7 months ago
Proximal regularization for online and batch learning
Many learning algorithms rely on the curvature (in particular, strong convexity) of regularized objective functions to provide good theoretical performance guarantees. In practice...
Chuong B. Do, Quoc V. Le, Chuan-Sheng Foo
FMICS
2007
Springer
16 years 16 days ago
Machine Checked Formal Proof of a Scheduling Protocol for Smartcard Personalization
Using PVS (Prototype Verification System), we prove that an industry designed scheduler for a smartcard personalization machine is safe and optimal. This scheduler has previously ...
Leonard Lensink, Sjaak Smetsers, Marko C. J. D. va...
176
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SIGSOFT
2009
ACM
16 years 7 months ago
Probabilistic environments in the quantitative analysis of (non-probabilistic) behaviour models
System specifications have long been expressed through automata-based languages, enabling verification techniques such as model checking. These verification techniques can assess ...
Esteban Pavese, Sebastián Uchitel, Ví...
TACAS
2004
Springer
111views Algorithms» more  TACAS 2004»
15 years 11 months ago
Automatic Creation of Environment Models via Training
Abstract. Model checking suffers not only from the state-space explosion problem, but also from the environment modeling problem: how can one create an accurate enough model of the...
Thomas Ball, Vladimir Levin, Fei Xie
ICASSP
2011
IEEE
14 years 10 months ago
Maximum a posteriori based regularization parameter selection
The 1 norm regularized least square technique has been proposed as an efficient method to calculate sparse solutions. However, the choice of the regularization parameter is still...
Ashkan Panahi, Mats Viberg