Shenglong Zhou

CoRR, 2024

Communication-Efficient Decentralized Federated Learning via One-Bit Compressive Sensing.

[BibT_eX]

[DOI]

Kaidi Xu

Proceedings of the 99th IEEE Vehicular Technology Conference, 2024

Federated Reinforcement Learning for Resource Allocation in V2X Networks.

[BibT_eX]

[DOI]

Kaidi Xu

Proceedings of the 99th IEEE Vehicular Technology Conference, 2024

2023

Federated Learning Via Inexact ADMM.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., August, 2023

FedGiA: An Efficient Hybrid Algorithm for Federated Learning.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2023

Gradient projection Newton algorithm for sparse collaborative learning using synthetic and real datasets of applications.

[BibT_eX]

[DOI]

Jun Sun

Lingchen Kong

J. Comput. Appl. Math., 2023

New Environment Adaptation with Few Shots for OFDM Receiver and mmWave Beamforming.

[BibT_eX]

[DOI]

CoRR, 2023

Effective Adaptation into New Environment with Few Shots: Applications to OFDM Receiver Design.

[BibT_eX]

[DOI]

Proceedings of the 33rd IEEE International Workshop on Machine Learning for Signal Processing, 2023

Few-Shot Learning for New Environment Adaptation.

[BibT_eX]

[DOI]

Proceedings of the IEEE Global Communications Conference, 2023

2022

Computing One-Bit Compressive Sensing via Double-Sparsity Constrained Optimization.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2022

Sparse SVM for Sufficient Data Reduction.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Support Vector Machine Classifier via $L_{0/1}$L0/1 Soft-Margin Loss.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Semismooth Newton-type method for bilevel optimization: global convergence and extensive numerical experiments.

[BibT_eX]

[DOI]

Andreas Fischer

Alain B. Zemkoho

Optim. Methods Softw., 2022

Exact Penalty Method for Federated Learning.

[BibT_eX]

[DOI]

CoRR, 2022

0/1 Deep Neural Networks via Block Coordinate Descent.

[BibT_eX]

[DOI]

CoRR, 2022

Efficient and Convergent Federated Learning.

[BibT_eX]

[DOI]

CoRR, 2022

2021

Newton Hard-Thresholding Pursuit for Sparse Linear Complementarity Problem via A New Merit Function.

[BibT_eX]

[DOI]

SIAM J. Sci. Comput., 2021

Quadratic Convergence of Smoothing Newton's Method for 0/1 Loss Optimization.

[BibT_eX]

[DOI]

SIAM J. Optim., 2021

Newton method for ℓ<sub>0</sub>-regularized optimization.

[BibT_eX]

[DOI]

Lili Pan

Numer. Algorithms, 2021

Global and Quadratic Convergence of Newton Hard-Thresholding Pursuit.

[BibT_eX]

[DOI]

Hou-Duo Qi

J. Mach. Learn. Res., 2021

An extended Newton-type algorithm for ℓ2-regularized sparse logistic regression and its efficiency for classifying large-scale datasets.

[BibT_eX]

[DOI]

Rui Wang

J. Comput. Appl. Math., 2021

Accretionary Learning with Deep Neural Networks.

[BibT_eX]

[DOI]

Xinyu Wei

Biing-Hwang Fred Juang

CoRR, 2021

Communication-Efficient ADMM-based Federated Learning.

[BibT_eX]

[DOI]

CoRR, 2021

Theoretical and numerical comparison of the Karush-Kuhn-Tucker and value function reformulations in bilevel optimization.

[BibT_eX]

[DOI]

Alain B. Zemkoho

Comput. Optim. Appl., 2021

2020

Robust Euclidean embedding via EDM optimization.

[BibT_eX]

[DOI]

Hou-Duo Qi

Math. Program. Comput., 2020

Matrix Optimization Over Low-Rank Spectral Sets: Stationary Points and Local and Global Minimizers.

[BibT_eX]

[DOI]

Xinrong Li

J. Optim. Theory Appl., 2020

2019

Support Vector Machine Classifier via L<sub>0/1</sub> Soft-Margin Loss.

[BibT_eX]

[DOI]

CoRR, 2019

2018

A Fast Matrix Majorization-Projection Method for Penalized Stress Minimization With Box Constraints.

[BibT_eX]

[DOI]