activity
20202026
most citedImproving the Transferability of Adversarial Examples with Resized-Diverse-Inputs, Diversity-Ensemble and Region Fitting

61 citations · 72 across the 7 of their papers we have counts for

collaborators

8 papers

cs.LG2026

HyBRA-EEG: Hyperbolic Global-Local Brain-Region Aggregation for Self-Supervised EEG Representation Learning

Xin Liu, Feng Lu, Wei Li

Electroencephalography (EEG) representation learning is challenged by noisy signals, inter-subject variability, and heterogeneous electrode montages in different datasets and recor…

cs.LG2023

On the Convergence of Federated Averaging under Partial Participation for Over-parameterized Neural Networks

Xin Liu, Wei li, Dazhi Zhan +4

Federated learning (FL) is a widely employed distributed paradigm for collaboratively training machine learning models from multiple clients without sharing local data. In practice…

cs.LG2022★ 3 cited

Provable Acceleration of Nesterov's Accelerated Gradient Method over Heavy Ball Method in Training Over-Parameterized Neural Networks

Xin Liu, Wei Tao, Wei Li +3

Due to its simplicity and efficiency, the first-order gradient method has been extensively employed in training neural networks. Although the optimization problem of the neural net…

cs.LG2022★ 7 cited

FedSSO: A Federated Server-Side Second-Order Optimization Algorithm

Xin Ma, Renyi Bao, Jinpeng Jiang +5

In this work, we propose FedSSO, a server-side second-order optimization method for federated learning (FL). In contrast to previous works in this direction, we employ a server-sid…

cs.LG2022

A Convergence Analysis of Nesterov's Accelerated Gradient Method in Training Deep Linear Neural Networks

Xin Liu, Wei Tao, Zhisong Pan

Momentum methods, including heavy-ball~(HB) and Nesterov's accelerated gradient~(NAG), are widely used in training neural networks for their fast convergence. However, there is a l…

cs.CV2021★ 61 cited

Improving the Transferability of Adversarial Examples with Resized-Diverse-Inputs, Diversity-Ensemble and Region Fitting

Junhua Zou, Zhisong Pan, Junyang Qiu +3

We introduce a three stage pipeline: resized-diverse-inputs (RDIM), diversity-ensemble (DEM) and region fitting, that work together to generate transferable adversarial examples. W…

cs.LG2021

Provable Convergence of Nesterov's Accelerated Gradient Method for Over-Parameterized Neural Networks

Xin Liu, Zhisong Pan, Wei Tao

Momentum methods, such as heavy ball method~(HB) and Nesterov's accelerated gradient method~(NAG), have been widely used in training neural networks by incorporating the history of…

cs.CV2020★ 1 cited

Making Adversarial Examples More Transferable and Indistinguishable

Junhua Zou, Yexin Duan, Boyu Li +3

Fast gradient sign attack series are popular methods that are used to generate adversarial examples. However, most of the approaches based on fast gradient sign attack series canno…