Statistical Machine Learning Lab

Princeton University

Nonparametric Structure Learning

Keywords: combinatorial inference, .


Infering the topological and geometrical properties of high dimensional nonparametric graphical models.

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Nonparametric Representation Learning

Keywords: dynamic regularization.


Learning the nonparametric representation of the data using stochastic and algorithmic regularization.

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Nonconvex Statistical Optimization

Keywords: model based optimization.


A model based approach to explore the interactions between informational and computational complexity.

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Data enabled Science and Machine Intelligence

Keywords: genomics, neuroimage, financial time series, and social media.


Post-regularization or post-selection inference with controlled false discovery rate. Extracting commonality from massive amounts of hetergenous datasets

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We currently highlight:

A Framework for Post-Regularization Inference

Dec 15th, 2014 | Paper

Yang Ning and Han Liu.

The Nonparanormal SKEPTIC

Feb 10th, 2012 | Paper

Han Liu, Fang Han, Ming Yuan, John Lafferty, and Larry Wasserman

Reading Group

We have biweekly reading group. The topics of this semeser include optimization in infinite dimensional space, homotopy algorithm, stochastic convex optimization, random matrix theory, and CUDA for GPU programming.

Get In Touch

Department of Operations Research and Financial Engineering
Sherred Hall 224
Princeton University, NJ 08544
Phone: +609 258 1788