b'Yun Yang'

research

∙ 06/01/2023

On the Convergence of Coordinate Ascent Variational Inference

As a computational alternative to Markov chain Monte Carlo approaches, v...

0 Anirban Bhattacharya, et al. ∙

research

∙ 05/30/2023

CTSN: Predicting Cloth Deformation for Skeleton-based Characters with a Two-stream Skinning Network

We present a novel learning method to predict the cloth deformation for ...

0 Yudi Li, et al. ∙

research

∙ 05/29/2023

Statistically Optimal K-means Clustering via Nonnegative Low-rank Semidefinite Programming

K-means clustering is a widely used machine learning method for identify...

0 Yubo Zhuang, et al. ∙

research

∙ 05/15/2023

Global and Local Mixture Consistency Cumulative Learning for Long-tailed Visual Recognitions

In this paper, our goal is to design a simple learning paradigm for long...

0 Fei Du, et al. ∙

research

∙ 02/15/2023

TFormer: A Transmission-Friendly ViT Model for IoT Devices

Deploying high-performance vision transformer (ViT) models on ubiquitous...

2 Zhichao Lu, et al. ∙

research

∙ 01/02/2023

Estimating Distributions with Low-dimensional Structures Using Mixtures of Generative Models

There has been a growing interest in statistical inference from data sat...

0 Rong Tang, et al. ∙

research

∙ 09/29/2022

Likelihood adjusted semidefinite programs for clustering heterogeneous data

Clustering is a widely deployed unsupervised learning tool. Model-based ...

0 Yubo Zhuang, et al. ∙

research

∙ 09/14/2022

Wasserstein K-means for clustering probability distributions

Clustering is an important exploratory data analysis technique to group ...

0 Yubo Zhuang, et al. ∙

research

∙ 07/17/2022

Mean field Variational Inference via Wasserstein Gradient Flow

Variational inference (VI) provides an appealing alternative to traditio...

0 Rentian Yao, et al. ∙

research

∙ 06/13/2022

On the Computational Complexity of Metropolis-Adjusted Langevin Algorithms for Bayesian Posterior Sampling

In this paper, we study the computational complexity of sampling from a ...

0 Rong Tang, et al. ∙

research

∙ 05/16/2022

Mean-Field Nonparametric Estimation of Interacting Particle Systems

This paper concerns the nonparametric estimation problem of the distribu...

0 Rentian Yao, et al. ∙

research

∙ 02/18/2022

Minimax Rate of Distribution Estimation on Unknown Submanifold under Adversarial Losses

Statistical inference from high-dimensional data with low-dimensional st...

0 Rong Tang, et al. ∙

research

∙ 01/20/2022

Sketch-and-Lift: Scalable Subsampled Semidefinite Program for K-means Clustering

Semidefinite programming (SDP) is a powerful tool for tackling a wide ra...

0 Yubo Zhuang, et al. ∙

research

∙ 12/13/2021

N-Cloth: Predicting 3D Cloth Deformation with Mesh-Based Networks

We present a novel mesh-based learning approach (N-Cloth) for plausible ...

16 Yudi Li, et al. ∙

research

∙ 10/08/2021

Learning Topic Models: Identifiability and Finite-Sample Analysis

Topic models provide a useful text-mining tool for learning, extracting ...

0 Yinyin Chen, et al. ∙

research

∙ 09/23/2021

Regret Lower Bound and Optimal Algorithm for High-Dimensional Contextual Linear Bandit

In this paper, we consider the multi-armed bandit problem with high-dime...

0 Ke Li, et al. ∙

research

∙ 09/16/2021

Statistical Inference for Bayesian Risk Minimization via Exponentially Tilted Empirical Likelihood

The celebrated Bernstein von-Mises theorem ensures that credible regions...

0 Rong Tang, et al. ∙

research

∙ 08/20/2021

AdvDrop: Adversarial Attack to DNNs by Dropping Information

Human can easily recognize visual objects with lost information: even lo...

3 Ranjie Duan, et al. ∙

research

∙ 07/26/2021

Cost-effective Land Cover Classification for Remote Sensing Images

Land cover maps are of vital importance to various fields such as land u...

0 Dongwei Li, et al. ∙

research

∙ 03/11/2021

Adversarial Laser Beam: Effective Physical-World Attack to DNNs in a Blink

Though it is well known that the performance of deep neural networks (DN...

0 Ranjie Duan, et al. ∙

research

∙ 02/26/2021

Class Knowledge Overlay to Visual Feature Learning for Zero-Shot Image Classification

New categories can be discovered by transforming semantic features into ...

0 Cheng Xie, et al. ∙

research

∙ 02/23/2021

Multi-Knowledge Fusion for New Feature Generation in Generalized Zero-Shot Learning

Suffering from the semantic insufficiency and domain-shift problems, mos...

0 Hongxin Xiang, et al. ∙

research

∙ 01/30/2021

EdgeWorkflowReal: An Edge Computing based Workflow Execution Engine for Smart Systems

Current cloud-based smart systems suffer from weaknesses such as high re...

0 Xuejun Li, et al. ∙

research

∙ 01/25/2021

Cross Knowledge-based Generative Zero-Shot Learning Approach with Taxonomy Regularization

Although zero-shot learning (ZSL) has an inferential capability of recog...

6 Cheng Xie, et al. ∙

research

∙ 09/22/2020

Efficiently Finding a Maximal Clique Summary via Effective Sampling

Maximal clique enumeration (MCE) is a fundamental problem in graph theor...

0 Xiaofan Li, et al. ∙

research

∙ 09/06/2020

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...

19 Po Yang, et al. ∙

research

∙ 04/26/2020

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

Compared with traditional machine learning methods, deep learning method...

6 Xiangdong Zhang, et al. ∙

research

∙ 04/05/2020

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

The growing size of modern data sets brings many challenges to the exist...

10 Xi Chen, et al. ∙

research

∙ 01/05/2020

Cutoff for exact recovery of Gaussian mixture models

We determine the cutoff value on separation of cluster centers for exact...

0 Xiaohui Chen, et al. ∙

research

∙ 11/04/2019

Statistical Inference in Mean-Field Variational Bayes

We conduct non-asymptotic analysis on the mean-field variational inferen...

13 Wei Han, et al. ∙

research

∙ 10/14/2019

Gaussian Processes with Errors in Variables: Theory and Computation

Covariate measurement error in nonparametric regression is a common prob...

0 Shuang Zhou, et al. ∙

research

∙ 09/26/2019

Model-based Statistical Depth with Applications to Functional Data

Statistical depth, a commonly used analytic tool in non-parametric stati...

0 Weilong Zhao, et al. ∙

research

∙ 09/22/2019

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

Clustering big data often requires tremendous computational resources wh...

0 Dongwei Li, et al. ∙

research

∙ 07/26/2019

Edge User Allocation with Dynamic Quality of Service

In edge computing, edge servers are placed in close proximity to end-use...

0 Phu Lai, et al. ∙

research

∙ 04/11/2019

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

In mobile edge computing, edge servers are geographically distributed ar...

0 Phu Lai, et al. ∙

research

∙ 03/22/2019

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

We consider Hadamard product parametrization as a change-of-variable (ov...

0 Peng Zhao, et al. ∙

research

∙ 03/11/2019

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

We introduce the diffusion K-means clustering method on Riemannian subm...

0 Xiaohui Chen, et al. ∙

research

∙ 10/26/2018

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...

0 Xiaohui Chen, et al. ∙

research

∙ 12/25/2017

On Statistical Optimality of Variational Bayes

The article addresses a long-standing open problem on the justification ...

0 Debdeep Pati, et al. ∙

research

∙ 10/09/2017

α-Variational Inference with Statistical Guarantees

We propose a variational approximation to Bayesian posterior distributio...

0 Yun Yang, et al. ∙

research

∙ 08/16/2017

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

Gaussian process (GP) regression is a powerful interpolation technique d...

0 Yun Yang, et al. ∙

research

∙ 04/17/2017

Statistical inference for high dimensional regression via Constrained Lasso

In this paper, we propose a new method for estimation and constructing c...

0 Yun Yang, et al. ∙

research

∙ 01/02/2017

Bayesian model selection consistency and oracle inequality with intractable marginal likelihood

In this article, we investigate large sample properties of model selecti...

0 Yun Yang, et al. ∙

research

∙ 05/25/2016

Communication-Efficient Distributed Statistical Inference

We present a Communication-efficient Surrogate Likelihood (CSL) framewor...

0 Michael I. Jordan, et al. ∙

research

∙ 05/29/2015

On the Computational Complexity of High-Dimensional Bayesian Variable Selection

We study the computational complexity of Markov chain Monte Carlo (MCMC)...

0 Yun Yang, et al. ∙

research

∙ 01/25/2015

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

Kernel ridge regression (KRR) is a standard method for performing non-pa...

0 Yun Yang, et al. ∙

research

∙ 03/06/2014

Minimax Optimal Bayesian Aggregation

It is generally believed that ensemble approaches, which combine multipl...

0 Yun Yang, et al. ∙

research

∙ 04/22/2013

Bayesian crack detection in ultra high resolution multimodal images of paintings

The preservation of our cultural heritage is of paramount importance. Th...

0 Bruno Cornelis, et al. ∙

Yun Yang

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