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» A scalable modular convex solver for regularized risk minimi...
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143
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KDD
2007
ACM
132views Data Mining» more  KDD 2007»
16 years 1 months ago
A scalable modular convex solver for regularized risk minimization
A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and different r...
Choon Hui Teo, Alex J. Smola, S. V. N. Vishwanatha...
112
Voted
JMLR
2010
135views more  JMLR 2010»
14 years 11 months ago
Bundle Methods for Regularized Risk Minimization
A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and differen...
Choon Hui Teo, S. V. N. Vishwanathan, Alex J. Smol...
127
Voted
JMLR
2010
143views more  JMLR 2010»
14 years 11 months ago
A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning
We extend the well-known BFGS quasi-Newton method and its memory-limited variant LBFGS to the optimization of nonsmooth convex objectives. This is done in a rigorous fashion by ge...
Jin Yu, S. V. N. Vishwanathan, Simon Günter, ...