Search Results for author: Yuancheng Zhu

Found 6 papers, 0 papers with code

Distributed Nonparametric Regression under Communication Constraints

no code implementations ICML 2018 Yuancheng Zhu, John Lafferty

In an intermediate regime, the statistical risk depends on both the sample size and the communication budget.

Uncertainty Quantification for Online Learning and Stochastic Approximation via Hierarchical Incremental Gradient Descent

no code implementations13 Feb 2018 Weijie J. Su, Yuancheng Zhu

Stochastic gradient descent (SGD) is an immensely popular approach for online learning in settings where data arrives in a stream or data sizes are very large.

Local Minimax Complexity of Stochastic Convex Optimization

no code implementations NeurIPS 2016 Yuancheng Zhu, Sabyasachi Chatterjee, John Duchi, John Lafferty

The bounds are expressed in terms of a localized and computational analogue of the modulus of continuity that is central to statistical minimax analysis.

Learning Nonparametric Forest Graphical Models with Prior Information

no code implementations12 Nov 2015 Yuancheng Zhu, Zhe Liu, Siqi Sun

We present a framework for incorporating prior information into nonparametric estimation of graphical models.

Density Estimation

Quantized Nonparametric Estimation over Sobolev Ellipsoids

no code implementations25 Mar 2015 Yuancheng Zhu, John Lafferty

We formulate the notion of minimax estimation under storage or communication constraints, and prove an extension to Pinsker's theorem for nonparametric estimation over Sobolev ellipsoids.

Quantization

Quantized Estimation of Gaussian Sequence Models in Euclidean Balls

no code implementations NeurIPS 2014 Yuancheng Zhu, John Lafferty

A central result in statistical theory is Pinsker's theorem, which characterizes the minimax rate in the normal means model of nonparametric estimation.

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