research
∙
07/29/2023
Catching Elusive Depression via Facial Micro-Expression Recognition
Depression is a common mental health disorder that can cause consequenti...
share
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...
research
∙
05/25/2023
Graph-Based Model-Agnostic Data Subsampling for Recommendation Systems
Data subsampling is widely used to speed up the training of large-scale ...
research
∙
05/06/2023
Efficient and Degree-Guided Graph Generation via Discrete Diffusion Modeling
Diffusion-based generative graph models have been proven effective in ge...
research
∙
12/03/2022
Interpretable Node Representation with Attribute Decoding
Variational Graph Autoencoders (VGAEs) are powerful models for unsupervi...
research
∙
11/19/2022
NVDiff: Graph Generation through the Diffusion of Node Vectors
Learning to generate graphs is challenging as a graph is a set of pairwi...
research
∙
09/29/2022
Likelihood adjusted semidefinite programs for clustering heterogeneous data
Clustering is a widely deployed unsupervised learning tool. Model-based ...
research
∙
09/28/2022
GeONet: a neural operator for learning the Wasserstein geodesic
Optimal transport (OT) offers a versatile framework to compare complex d...
research
∙
09/14/2022
Wasserstein K-means for clustering probability distributions
Clustering is an important exploratory data analysis technique to group ...
research
∙
05/16/2022
Mean-Field Nonparametric Estimation of Interacting Particle Systems
This paper concerns the nonparametric estimation problem of the distribu...
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...
research
∙
09/15/2021
A Framework for Multisensory Foresight for Embodied Agents
Predicting future sensory states is crucial for learning agents such as ...
research
∙
06/11/2021
Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation
A graph generative model defines a distribution over graphs. One type of...
research
∙
04/27/2021
Central Limit Theorems for High Dimensional Dependent Data
Motivated by statistical inference problems in high-dimensional time ser...
research
∙
12/14/2020
GAN Ensemble for Anomaly Detection
When formulated as an unsupervised learning problem, anomaly detection o...
research
∙
07/21/2020
Maximum likelihood estimation of potential energy in interacting particle systems from single-trajectory data
This paper concerns the parameter estimation problem for the quadratic p...
research
∙
04/07/2020
Scenario analysis of non-pharmaceutical interventions on global COVID-19 transmissions
This paper introduces a dynamic panel SIR (DP-SIR) model to investigate ...
research
∙
03/20/2020
Stratified incomplete local simplex tests for curvature of nonparametric multiple regression
Principled nonparametric tests for regression curvature in R^d are often...
research
∙
02/21/2020
A note on Stein equation for weighted sums of independent χ^2 distributions
This note provides the Stein equation for weighted sums of independent χ...
research
∙
02/20/2020
Robust M-estimation for Partially Observed Functional Data
Irregular functional data in which densely sampled curves are observed o...
research
∙
01/05/2020
Cutoff for exact recovery of Gaussian mixture models
We determine the cutoff value on separation of cluster centers for exact...
research
∙
11/14/2019
Estimation of dynamic networks for high-dimensional nonstationary time series
This paper is concerned with the estimation of time-varying networks for...
research
∙
06/15/2019
An End-to-End Block Autoencoder For Physical Layer Based On Neural Networks
Deep Learning has been widely applied in the area of image processing an...
research
∙
04/06/2019
A robust bootstrap change point test for high-dimensional location parameter
We consider the problem of change point detection for high-dimensional d...
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...
research
∙
01/04/2019
Approximating high-dimensional infinite-order U-statistics: statistical and computational guarantees
We study the problem of distributional approximations to high-dimensiona...
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...
research
∙
04/08/2018
TCP Decoupling for Next Generation Communication System
In traditional networks, interfaces of network nodes are duplex. But, em...
research
∙
03/01/2018
Rate Loss of Hybrid Beamforming with Imperfect Phase Shifters in Millimeter Wave Systems
In millimeter massive MIMO systems, hybrid beamforming algorithms with f...
research
∙
01/12/2018
Comprehensive Optimization of Parametric Kernels for Graphics Processing Units
This work deals with the optimization of computer programs targeting Gra...
research
∙
12/03/2017
Randomized incomplete U-statistics in high dimensions
This paper studies inference for the mean vector of a high-dimensional U...
research
∙
11/23/2017
