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06/01/2023
On the Convergence of Coordinate Ascent Variational Inference
As a computational alternative to Markov chain Monte Carlo approaches, v...
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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 ...
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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...
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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...
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02/15/2023
TFormer: A Transmission-Friendly ViT Model for IoT Devices
Deploying high-performance vision transformer (ViT) models on ubiquitous...
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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...
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09/29/2022
Likelihood adjusted semidefinite programs for clustering heterogeneous data
Clustering is a widely deployed unsupervised learning tool. Model-based ...
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09/14/2022
Wasserstein K-means for clustering probability distributions
Clustering is an important exploratory data analysis technique to group ...
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07/17/2022
Mean field Variational Inference via Wasserstein Gradient Flow
Variational inference (VI) provides an appealing alternative to traditio...
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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 ...
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05/16/2022
Mean-Field Nonparametric Estimation of Interacting Particle Systems
This paper concerns the nonparametric estimation problem of the distribu...
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02/18/2022
Minimax Rate of Distribution Estimation on Unknown Submanifold under Adversarial Losses
Statistical inference from high-dimensional data with low-dimensional st...
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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...
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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 ...
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10/08/2021
Learning Topic Models: Identifiability and Finite-Sample Analysis
Topic models provide a useful text-mining tool for learning, extracting ...
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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...
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09/16/2021
Statistical Inference for Bayesian Risk Minimization via Exponentially Tilted Empirical Likelihood
The celebrated Bernstein von-Mises theorem ensures that credible regions...
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08/20/2021
AdvDrop: Adversarial Attack to DNNs by Dropping Information
Human can easily recognize visual objects with lost information: even lo...
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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...
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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...
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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 ...
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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...
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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...
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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...
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09/22/2020
Efficiently Finding a Maximal Clique Summary via Effective Sampling
Maximal clique enumeration (MCE) is a fundamental problem in graph theor...
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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...
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04/26/2020
Hyperspectral image classification based on multi-scale residual network with attention mechanism
Compared with traditional machine learning methods, deep learning method...
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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...
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01/05/2020
Cutoff for exact recovery of Gaussian mixture models
We determine the cutoff value on separation of cluster centers for exact...
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11/04/2019
Statistical Inference in Mean-Field Variational Bayes
We conduct non-asymptotic analysis on the mean-field variational inferen...
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10/14/2019
Gaussian Processes with Errors in Variables: Theory and Computation
Covariate measurement error in nonparametric regression is a common prob...
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09/26/2019
Model-based Statistical Depth with Applications to Functional Data
Statistical depth, a commonly used analytic tool in non-parametric stati...
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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...
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07/26/2019
Edge User Allocation with Dynamic Quality of Service
In edge computing, edge servers are placed in close proximity to end-use...
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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...
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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...
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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...
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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...
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12/25/2017
On Statistical Optimality of Variational Bayes
The article addresses a long-standing open problem on the justification ...
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10/09/2017
α-Variational Inference with Statistical Guarantees
We propose a variational approximation to Bayesian posterior distributio...
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08/16/2017
Frequentist coverage and sup-norm convergence rate in Gaussian process regression
Gaussian process (GP) regression is a powerful interpolation technique d...
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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...
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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...
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05/25/2016
Communication-Efficient Distributed Statistical Inference
We present a Communication-efficient Surrogate Likelihood (CSL) framewor...
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05/29/2015
On the Computational Complexity of High-Dimensional Bayesian Variable Selection
We study the computational complexity of Markov chain Monte Carlo (MCMC)...
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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...
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03/06/2014
Minimax Optimal Bayesian Aggregation
It is generally believed that ensemble approaches, which combine multipl...
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04/22/2013
