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» Explicit and Implicit Enforcing - Randomized Optimization
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SIAMJO
2000
108views more  SIAMJO 2000»
13 years 7 months ago
Smooth SQP Methods for Mathematical Programs with Nonlinear Complementarity Constraints
Mathematical programs with nonlinear complementarity constraints are reformulated using better-posed but nonsmooth constraints. We introduce a class of functions, parameterized by...
Houyuan Jiang, Daniel Ralph
ICDM
2010
IEEE
200views Data Mining» more  ICDM 2010»
13 years 4 months ago
Bayesian Maximum Margin Clustering
Abstract--Most well-known discriminative clustering models, such as spectral clustering (SC) and maximum margin clustering (MMC), are non-Bayesian. Moreover, they merely considered...
Bo Dai, Baogang Hu, Gang Niu
TNN
2010
155views Management» more  TNN 2010»
13 years 2 months ago
Incorporating the loss function into discriminative clustering of structured outputs
Clustering using the Hilbert Schmidt independence criterion (CLUHSIC) is a recent clustering algorithm that maximizes the dependence between cluster labels and data observations ac...
Wenliang Zhong, Weike Pan, James T. Kwok, Ivor W. ...
SOSP
2007
ACM
14 years 4 months ago
Generalized file system dependencies
Reliable storage systems depend in part on “write-before” relationships where some changes to stable storage are delayed until other changes commit. A journaled file system, ...
Christopher Frost, Mike Mammarella, Eddie Kohler, ...
IPPS
2005
IEEE
14 years 1 months ago
Automatic Support for Irregular Computations in a High-Level Language
The problem of writing high performance parallel applications becomes even more challenging when irregular, sparse or adaptive methods are employed. In this paper we introduce com...
Jimmy Su, Katherine A. Yelick