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Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
Distributed Optimization Statistical Learning via Alternating Direction Method Multipliers
2015/7/9
Many problems of recent interest in statistics and machine learning can be posed in the framework of convex optimization. Due to the explosion in size and complexity of modern datasets, it is increasi...
Risk bounds for statistical learning
Classification concentration inequalities empirical processes entropy with bracketing minimax estimation
2010/4/26
We propose a general theorem providing upper bounds for the
risk of an empirical risk minimizer (ERM).We essentially focus on
the binary classification framework. We extend Tsybakov’s analysis
of t...
Best subset selection，persistence in high-dimensional statistical learning and optimization under L1 constraint
Variable selection persistence
2010/4/26
Let (Y,X1, . . . ,Xm) be a random vector. It is desired to predict Y
based on (X1, . . . ,Xm). Examples of prediction methods are regression,
classification using logistic regression or separating h...