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114
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ML
2002
ACM
167views Machine Learning» more  ML 2002»
14 years 11 months ago
Linear Programming Boosting via Column Generation
We examine linear program (LP) approaches to boosting and demonstrate their efficient solution using LPBoost, a column generation based simplex method. We formulate the problem as...
Ayhan Demiriz, Kristin P. Bennett, John Shawe-Tayl...
POPL
2005
ACM
15 years 12 months ago
Automated soundness proofs for dataflow analyses and transformations via local rules
We present Rhodium, a new language for writing compiler optimizations that can be automatically proved sound. Unlike our previous work on Cobalt, Rhodium expresses optimizations u...
Sorin Lerner, Todd D. Millstein, Erika Rice, Craig...
85
Voted
PPDP
2007
Springer
15 years 5 months ago
Unfolding in CHR
Program transformation is an appealing technique which allows to improve run-time efficiency, space-consumption and more generally to optimize a given program. Essentially it con...
Paolo Tacchella, Maurizio Gabbrielli, Maria Chiara...
ESOP
2006
Springer
15 years 3 months ago
Coinductive Big-Step Operational Semantics
Using a call-by-value functional language as an example, this article illustrates the use of coinductive definitions and proofs in big-step operational semantics, enabling it to d...
Xavier Leroy
124
Voted
JMLR
2012
13 years 2 months ago
Metric and Kernel Learning Using a Linear Transformation
Metric and kernel learning arise in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional d...
Prateek Jain, Brian Kulis, Jason V. Davis, Inderji...