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《The Elements of Statistical Learning: Data Mining, Inference, and Prediction》 (Second Edition)（图）
Data Mining Inference Prediction
2015/8/21
During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and mark...
《An Introduction to Statistical Learning with Applications in R》（图）
Statistical Learning Applications
2015/8/21
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged ...
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...
Detecting Events and Patterns in Large-Scale User Generated Textual Streams with Statistical Learning Methods
Detecting Events Patterns Large-Scale User Generated Textual Streams Statistical Learning Methods
2012/9/18
A vast amount of textual web streams is influenced by events or phenomena emerging in the real world. The social web forms an excellent modern paradigm, where unstructured user generated content is pu...
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...