Xiangyu Chang

Orcid: 0000-0001-9225-0477

According to our database1, Xiangyu Chang authored at least 58 papers between 2010 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2024
Fedpower: privacy-preserving distributed eigenspace estimation.
Mach. Learn., December, 2024

Digital Twins in Transportation Infrastructure: An Investigation of the Key Enabling Technologies, Applications, and Challenges.
IEEE Trans. Intell. Transp. Syst., July, 2024

On the efficacy of higher-order spectral clustering under weighted stochastic block models.
Comput. Stat. Data Anal., February, 2024

Kernel Interpolation of High Dimensional Scattered Data.
SIAM J. Numer. Anal., 2024

Accelerated Double-Sketching Subspace Newton.
Eur. J. Oper. Res., 2024

Spectral co-clustering in multi-layer directed networks.
Comput. Stat. Data Anal., 2024

Towards Data Valuation via Asymmetric Data Shapley.
CoRR, 2024

AdapFair: Ensuring Continuous Fairness for Machine Learning Operations.
CoRR, 2024

Uncertainty Quantification of Data Shapley via Statistical Inference.
CoRR, 2024

FLASH: Federated Learning Across Simultaneous Heterogeneities.
CoRR, 2024

Plug-and-Play Transformer Modules for Test-Time Adaptation.
CoRR, 2024

CONTRAST: Continual Multi-source Adaptation to Dynamic Distributions.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Selective Attention: Enhancing Transformer through Principled Context Control.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Clustered Federated Learning for Massive MIMO Power Allocation.
Proceedings of the IEEE Military Communications Conference, 2024

Double Variance Reduction: A Smoothing Trick for Composite Optimization Problems without First-Order Gradient.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Double Stochasticity Gazes Faster: Snap-Shot Decentralized Stochastic Gradient Tracking Methods.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Accelerated Distributed Approximate Newton Method.
IEEE Trans. Neural Networks Learn. Syst., November, 2023

Multi-step reward ensemble methods for adaptive stock trading.
Expert Syst. Appl., November, 2023

Variance reduced Shapley value estimation for trustworthy data valuation.
Comput. Oper. Res., November, 2023

Towards explicit superlinear convergence rate for SR1.
Math. Program., May, 2023

Randomized Spectral Co-Clustering for Large-Scale Directed Networks.
J. Mach. Learn. Res., 2023

PPFL: A Personalized Federated Learning Framework for Heterogeneous Population.
CoRR, 2023

Causal Rule Learning: Enhancing the Understanding of Heterogeneous Treatment Effect via Weighted Causal Rules.
CoRR, 2023

FedYolo: Augmenting Federated Learning with Pretrained Transformers.
CoRR, 2023

Privacy-Preserving Community Detection for Locally Distributed Multiple Networks.
CoRR, 2023

Learning Personalized Brain Functional Connectivity of MDD Patients from Multiple Sites via Federated Bayesian Networks.
CoRR, 2023

2D-Shapley: A Framework for Fragmented Data Valuation.
Proceedings of the International Conference on Machine Learning, 2023

Federated Learning for Massive MIMO Power Allocation.
Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023

2022
Randomized Spectral Clustering in Large-Scale Stochastic Block Models.
J. Comput. Graph. Stat., July, 2022

Learning With Selected Features.
IEEE Trans. Cybern., 2022

Robust Data Valuation via Variance Reduced Data Shapley.
CoRR, 2022

Learning Multitask Gaussian Bayesian Networks.
CoRR, 2022

Statistical Estimation and Online Inference via Local SGD.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021
Privacy-Preserving Cost-Sensitive Learning.
IEEE Trans. Neural Networks Learn. Syst., 2021

Understanding the complexity of sepsis mortality prediction via rule discovery and analysis: a pilot study.
BMC Medical Informatics Decis. Mak., 2021

SURVFIT: Doubly sparse rule learning for survival data.
J. Biomed. Informatics, 2021

Angle-based cost-sensitive multicategory classification.
Comput. Stat. Data Anal., 2021

Towards a Fairness-Aware Scoring System for Algorithmic Decision-Making.
CoRR, 2021

Statistical Estimation and Inference via Local SGD in Federated Learning.
CoRR, 2021

Privacy-Preserving Distributed SVD via Federated Power.
CoRR, 2021

Provable Benefits of Overparameterization in Model Compression: From Double Descent to Pruning Neural Networks.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2019
Unified Low-Rank Matrix Estimate via Penalized Matrix Least Squares Approximation.
IEEE Trans. Neural Networks Learn. Syst., 2019

2018
Predicting Depression Severity by Multi-Modal Feature Engineering and Fusion.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Sparse Regularization in Fuzzy c-Means for High-Dimensional Data Clustering.
IEEE Trans. Cybern., 2017

Learning Rates for Classification with Gaussian Kernels.
Neural Comput., 2017

Distributed Semi-supervised Learning with Kernel Ridge Regression.
J. Mach. Learn. Res., 2017

2016
Divide and Conquer Local Average Regression.
CoRR, 2016

An Empirical Research on Technostress Creators and End-User Performance: the Mediating Roles of Affective Attitudes.
Proceedings of the 20th Pacific Asia Conference on Information Systems, 2016

2015
Linear Convergence of Adaptively Iterative Thresholding Algorithms for Compressed Sensing.
IEEE Trans. Signal Process., 2015

Folded-concave penalization approaches to tensor completion.
Neurocomputing, 2015

2014
Sparse K-Means with ℓ<sub>∞</sub>/ℓ<sub>0</sub> Penalty for High-Dimensional Data Clustering.
CoRR, 2014

2013
Sparse K-Means with the l_q(0leq q< 1) Constraint for High-Dimensional Data Clustering.
Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

2012
L<sub>1/2</sub> Regularization: A Thresholding Representation Theory and a Fast Solver.
IEEE Trans. Neural Networks Learn. Syst., 2012

A general radial quasi-interpolation operator on the sphere.
J. Approx. Theory, 2012

Asymptotic Normality of Maximum Likelihood and its Variational Approximation for Stochastic Blockmodels
CoRR, 2012

Generalization bounds of ERM algorithm with V-geometrically Ergodic Markov chains.
Adv. Comput. Math., 2012

2011
Generalization Bounds of Regularization Algorithms Derived Simultaneously through Hypothesis Space Complexity, Algorithmic Stability and Data Quality.
Int. J. Wavelets Multiresolution Inf. Process., 2011

2010
<i>L</i><sub>1/2</sub> regularization.
Sci. China Inf. Sci., 2010


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