Yun Yang

MFL_COVID19: Quantifying Country-based Factors affecting Case Fatality Rate in Early Phase of COVID-19 Epidemic via Regularised Multi-task Feature Learning

Recent outbreak of COVID-19 has led a rapid global spread around the wor...
09/06/2020 ∙ by Po Yang, et al. ∙ 19 ∙ share

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Hyperspectral image classification based on multi-scale residual network with attention mechanism

Compared with traditional machine learning methods, deep learning method...
04/26/2020 ∙ by Xiangdong Zhang, et al. ∙ 6 ∙ share

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Distributed Estimation for Principal Component Analysis: a Gap-free Approach

The growing size of modern data sets brings many challenges to the exist...
04/05/2020 ∙ by Xi Chen, et al. ∙ 10 ∙ share

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Cutoff for exact recovery of Gaussian mixture models

We determine the cutoff value on separation of cluster centers for exact...
01/05/2020 ∙ by Xiaohui Chen, et al. ∙ 0 ∙ share

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Statistical Inference in Mean-Field Variational Bayes

We conduct non-asymptotic analysis on the mean-field variational inferen...
11/04/2019 ∙ by Wei Han, et al. ∙ 13 ∙ share

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Gaussian Processes with Errors in Variables: Theory and Computation

Covariate measurement error in nonparametric regression is a common prob...
10/14/2019 ∙ by Shuang Zhou, et al. ∙ 0 ∙ share

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Model-based Statistical Depth with Applications to Functional Data

Statistical depth, a commonly used analytic tool in non-parametric stati...
09/26/2019 ∙ by Weilong Zhao, et al. ∙ 0 ∙ share

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Cutting the Unnecessary Long Tail: Cost-Effective Big Data Clustering in the Cloud

Clustering big data often requires tremendous computational resources wh...
09/22/2019 ∙ by Dongwei Li, et al. ∙ 0 ∙ share

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Edge User Allocation with Dynamic Quality of Service

In edge computing, edge servers are placed in close proximity to end-use...
07/26/2019 ∙ by Phu Lai, et al. ∙ 0 ∙ share

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Optimal Edge User Allocation in Edge Computing with Variable Sized Vector Bin Packing

In mobile edge computing, edge servers are geographically distributed ar...
04/11/2019 ∙ by Phu Lai, et al. ∙ 0 ∙ share

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Implicit Regularization via Hadamard Product Over-Parametrization in High-Dimensional Linear Regression

We consider Hadamard product parametrization as a change-of-variable (ov...
03/22/2019 ∙ by Peng Zhao, et al. ∙ 0 ∙ share

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Diffusion K-means clustering on manifolds: provable exact recovery via semidefinite relaxations

We introduce the diffusion K-means clustering method on Riemannian subm...
03/11/2019 ∙ by Xiaohui Chen, et al. ∙ 0 ∙ share

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Hanson-Wright inequality in Hilbert spaces with application to K-means clustering for non-Euclidean data

We derive a dimensional-free Hanson-Wright inequality for quadratic form...
10/26/2018 ∙ by Xiaohui Chen, et al. ∙ 0 ∙ share

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On Statistical Optimality of Variational Bayes

The article addresses a long-standing open problem on the justification ...
12/25/2017 ∙ by Debdeep Pati, et al. ∙ 0 ∙ share

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α-Variational Inference with Statistical Guarantees

We propose a variational approximation to Bayesian posterior distributio...
10/09/2017 ∙ by Yun Yang, et al. ∙ 0 ∙ share

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Frequentist coverage and sup-norm convergence rate in Gaussian process regression

Gaussian process (GP) regression is a powerful interpolation technique d...
08/16/2017 ∙ by Yun Yang, et al. ∙ 0 ∙ share

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Statistical inference for high dimensional regression via Constrained Lasso

In this paper, we propose a new method for estimation and constructing c...
04/17/2017 ∙ by Yun Yang, et al. ∙ 0 ∙ share

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Bayesian model selection consistency and oracle inequality with intractable marginal likelihood

In this article, we investigate large sample properties of model selecti...
01/02/2017 ∙ by Yun Yang, et al. ∙ 0 ∙ share

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Communication-Efficient Distributed Statistical Inference

We present a Communication-efficient Surrogate Likelihood (CSL) framewor...
05/25/2016 ∙ by Michael I. Jordan, et al. ∙ 0 ∙ share

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On the Computational Complexity of High-Dimensional Bayesian Variable Selection

We study the computational complexity of Markov chain Monte Carlo (MCMC)...
05/29/2015 ∙ by Yun Yang, et al. ∙ 0 ∙ share

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Randomized sketches for kernels: Fast and optimal non-parametric regression

Kernel ridge regression (KRR) is a standard method for performing non-pa...
01/25/2015 ∙ by Yun Yang, et al. ∙ 0 ∙ share

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Minimax Optimal Bayesian Aggregation

It is generally believed that ensemble approaches, which combine multipl...
03/06/2014 ∙ by Yun Yang, et al. ∙ 0 ∙ share

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Bayesian crack detection in ultra high resolution multimodal images of paintings

The preservation of our cultural heritage is of paramount importance. Th...
04/22/2013 ∙ by Bruno Cornelis, et al. ∙ 0 ∙ share

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Yun Yang

Featured Co-authors

Michael I. Jordan

Xi Chen

Martin J. Wainwright

Wei Wu

David B. Dunson

Jason D. Lee

Joshua T. Vogelstein

Mert Pilanci

David Dunson

Wei Han

John Grundy

MFL_COVID19: Quantifying Country-based Factors affecting Case Fatality Rate in Early Phase of COVID-19 Epidemic via Regularised Multi-task Feature Learning

Hyperspectral image classification based on multi-scale residual network with attention mechanism

Distributed Estimation for Principal Component Analysis: a Gap-free Approach

Cutoff for exact recovery of Gaussian mixture models

Statistical Inference in Mean-Field Variational Bayes

Gaussian Processes with Errors in Variables: Theory and Computation

Model-based Statistical Depth with Applications to Functional Data

Cutting the Unnecessary Long Tail: Cost-Effective Big Data Clustering in the Cloud

Edge User Allocation with Dynamic Quality of Service

Optimal Edge User Allocation in Edge Computing with Variable Sized Vector Bin Packing

Implicit Regularization via Hadamard Product Over-Parametrization in High-Dimensional Linear Regression

Diffusion K-means clustering on manifolds: provable exact recovery via semidefinite relaxations

Hanson-Wright inequality in Hilbert spaces with application to K-means clustering for non-Euclidean data

On Statistical Optimality of Variational Bayes

α-Variational Inference with Statistical Guarantees

Frequentist coverage and sup-norm convergence rate in Gaussian process regression

Statistical inference for high dimensional regression via Constrained Lasso

Bayesian model selection consistency and oracle inequality with intractable marginal likelihood

Communication-Efficient Distributed Statistical Inference

On the Computational Complexity of High-Dimensional Bayesian Variable Selection

Randomized sketches for kernels: Fast and optimal non-parametric regression

Minimax Optimal Bayesian Aggregation

Bayesian crack detection in ultra high resolution multimodal images of paintings