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cs.LG2025
Preconditioned Inexact Stochastic ADMM for Deep Model
Shenglong Zhou, Ouya Wang, Ziyan Luo +2
Deep learning models are usually trained with stochastic gradient descent-based algorithms, but these optimizers face inherent limitations, such as slow convergence and stringent a…
cs.LG2024
BADM: Batch ADMM for Deep Learning
Ouya Wang, Shenglong Zhou, Geoffrey Ye Li
Stochastic gradient descent-based algorithms are widely used for training deep neural networks but often suffer from slow convergence. To address the challenge, we leverage the fra…
cs.LG2023★ 2 cited
Federated Reinforcement Learning for Resource Allocation in V2X Networks
Kaidi Xu, Shenglong Zhou, Geoffrey Ye Li
Resource allocation significantly impacts the performance of vehicle-to-everything (V2X) networks. Most existing algorithms for resource allocation are based on optimization or mac…