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CORR
2010
Springer
148views Education» more  CORR 2010»
13 years 5 months ago
A Unifying View of Multiple Kernel Learning
Recent research on multiple kernel learning has lead to a number of approaches for combining kernels in regularized risk minimization. The proposed approaches include different for...
Marius Kloft, Ulrich Rückert, Peter L. Bartle...
AAAI
2011
12 years 10 months ago
Convex Sparse Coding, Subspace Learning, and Semi-Supervised Extensions
Automated feature discovery is a fundamental problem in machine learning. Although classical feature discovery methods do not guarantee optimal solutions in general, it has been r...
Xinhua Zhang, Yaoliang Yu, Martha White, Ruitong H...
CDC
2009
IEEE
107views Control Systems» more  CDC 2009»
14 years 2 months ago
Learning approaches to the Witsenhausen counterexample from a view of potential games
— Since Witsenhausen put forward his remarkable counterexample in 1968, there have been many attempts to develop efficient methods for solving this non-convex functional optimiz...
Na Li, Jason R. Marden, Jeff S. Shamma
ICASSP
2009
IEEE
14 years 4 months ago
Map approach to learning sparse Gaussian Markov networks
Recently proposed l1-regularized maximum-likelihood optimization methods for learning sparse Markov networks result into convex problems that can be solved optimally and efficien...
Narges Bani Asadi, Irina Rish, Katya Scheinberg, D...
EMO
2009
Springer
159views Optimization» more  EMO 2009»
14 years 4 months ago
Recombination for Learning Strategy Parameters in the MO-CMA-ES
The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) is a variable-metric algorithm for real-valued vector optimization. It maintains a parent population...
Thomas Voß, Nikolaus Hansen, Christian Igel