Xiangyu Chang | DeepAI

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Featured Co-authors

Yi Yang
329 publications
Xi Chen
293 publications
Yu Wang
276 publications
Zhangyang Wang
245 publications
Bo Zhang
226 publications
Wei Huang
87 publications
Amit K. Roy-Chowdhury
64 publications
Samet Oymak
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Zongben Xu
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Christos Thrampoulidis
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Ananda Theertha Suresh
44 publications

∙ 07/20/2023

Spectral co-Clustering in Rank-deficient Multi-layer Stochastic co-Block Models

Modern network analysis often involves multi-layer network data in which...

0 Wenqing Su, et al. ∙

∙ 07/10/2023

FedYolo: Augmenting Federated Learning with Pretrained Transformers

The growth and diversity of machine learning applications motivate a ret...

0 Xuechen Zhang, et al. ∙

∙ 06/18/2023

2D-Shapley: A Framework for Fragmented Data Valuation

Data valuation – quantifying the contribution of individual data sources...

0 Zhihong Liu, et al. ∙

∙ 04/14/2023

Subsampling-Based Modified Bayesian Information Criterion for Large-Scale Stochastic Block Models

Identifying the number of communities is a fundamental problem in commun...

0 Jiayi Deng, et al. ∙

∙ 01/06/2023

Learning Personalized Brain Functional Connectivity of MDD Patients from Multiple Sites via Federated Bayesian Networks

Identifying functional connectivity biomarkers of major depressive disor...

0 Shuai Liu, et al. ∙

∙ 10/30/2022

Robust Data Valuation via Variance Reduced Data Shapley

Data valuation, especially quantifying data value in algorithmic predict...

0 Mengmeng Wu, et al. ∙

∙ 06/30/2022

On the efficacy of higher-order spectral clustering under weighted stochastic block models

Higher-order structures of networks, namely, small subgraphs of networks...

0 Xiao Guo, et al. ∙

∙ 05/11/2022

Learning Multitask Gaussian Bayesian Networks

Major depressive disorder (MDD) requires study of brain functional conne...

0 Shuai Liu, et al. ∙

∙ 09/21/2021

Towards a Fairness-Aware Scoring System for Algorithmic Decision-Making

Scoring systems, as simple classification models, have significant advan...

0 Yi Yang, et al. ∙

∙ 12/16/2020

Provable Benefits of Overparameterization in Model Compression: From Double Descent to Pruning Neural Networks

Deep networks are typically trained with many more parameters than the s...

0 Xiangyu Chang, et al. ∙

∙ 09/03/2020

Kernel Interpolation of High Dimensional Scattered Data

Data sites selected from modeling high-dimensional problems often appear...

0 Shao-Bo Lin, et al. ∙

∙ 04/25/2020

Randomized spectral co-clustering for large-scale directed networks

Directed networks are generally used to represent asymmetric relationshi...

0 Xiao Guo, et al. ∙

∙ 03/08/2020

Angle-Based Cost-Sensitive Multicategory Classification

Many real-world classification problems come with costs which can vary f...

0 Yi Yang, et al. ∙

∙ 01/20/2020

Randomized Spectral Clustering in Large-Scale Stochastic Block Models

Spectral clustering has been one of the widely used methods for communit...

0 Hai Zhang, et al. ∙

∙ 01/09/2020

Adaptive Stopping Rule for Kernel-based Gradient Descent Algorithms

In this paper, we propose an adaptive stopping rule for kernel-based gra...

0 Xiangyu Chang, et al. ∙

∙ 11/29/2017

Predicting Depression Severity by Multi-Modal Feature Engineering and Fusion

We present our preliminary work to determine if patient's vocal acoustic...

1 Aven Samareh, et al. ∙

∙ 02/28/2017

Learning rates for classification with Gaussian kernels

This paper aims at refined error analysis for binary classification usin...

0 Shao-Bo Lin, et al. ∙

∙ 03/31/2014

Sparse K-Means with ℓ_∞/ℓ_0 Penalty for High-Dimensional Data Clustering

Sparse clustering, which aims to find a proper partition of an extremely...

0 Xiangyu Chang, et al. ∙

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