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» Convex Learning with Invariances
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JMLR
2012
11 years 11 months ago
Beyond Logarithmic Bounds in Online Learning
We prove logarithmic regret bounds that depend on the loss L∗ T of the competitor rather than on the number T of time steps. In the general online convex optimization setting, o...
Francesco Orabona, Nicolò Cesa-Bianchi, Cla...
JMLR
2012
11 years 11 months ago
Marginal Regression For Multitask Learning
Variable selection is an important and practical problem that arises in analysis of many high-dimensional datasets. Convex optimization procedures that arise from relaxing the NP-...
Mladen Kolar, Han Liu
COLT
2004
Springer
14 years 2 months ago
Deterministic Calibration and Nash Equilibrium
Abstract. We provide a natural learning process in which the joint frequency of empirical play converges into the set of convex combinations of Nash equilibria. In this process, al...
Sham Kakade, Dean P. Foster
ICML
2009
IEEE
14 years 9 months ago
Learning structural SVMs with latent variables
We present a large-margin formulation and algorithm for structured output prediction that allows the use of latent variables. Our proposal covers a large range of application prob...
Chun-Nam John Yu, Thorsten Joachims
ESANN
2007
13 years 10 months ago
A metamorphosis of Canonical Correlation Analysis into multivariate maximum margin learning
Abstract. Canonical Correlation Analysis(CCA) is a useful tool to discover relationship between different sources of information represented by vectors. The solution of the underl...
Sándor Szedmák, Tijl De Bie, David R...