14 citations · 33 across the 6 of their papers we have counts for
6 papers
Sharper Convergence Guarantees for Federated Learning with Partial Model Personalization
Yiming Chen, Liyuan Cao, Kun Yuan +1
Partial model personalization, which encompasses both shared and personal variables in its formulation, is a critical optimization problem in federated learning. It balances indivi…
BEVHeight++: Toward Robust Visual Centric 3D Object Detection
Lei Yang, Tao Tang, Jun Li +6
While most recent autonomous driving system focuses on developing perception methods on ego-vehicle sensors, people tend to overlook an alternative approach to leverage intelligent…
AdaNPC: Exploring Non-Parametric Classifier for Test-Time Adaptation
Yi-Fan Zhang, Xue Wang, Kexin Jin +5
Many recent machine learning tasks focus to develop models that can generalize to unseen distributions. Domain generalization (DG) has become one of the key topics in various field…
BEVHeight: A Robust Framework for Vision-based Roadside 3D Object Detection
Lei Yang, Kaicheng Yu, Tao Tang +5
While most recent autonomous driving system focuses on developing perception methods on ego-vehicle sensors, people tend to overlook an alternative approach to leverage intelligent…
An Enhanced Gradient-Tracking Bound for Distributed Online Stochastic Convex Optimization
Sulaiman A. Alghunaim, Kun Yuan
Gradient-tracking (GT) based decentralized methods have emerged as an effective and viable alternative method to decentralized (stochastic) gradient descent (DSGD) when solving dis…
Decentralized Consensus Optimization with Asynchrony and Delays
Tianyu Wu, Kun Yuan, Qing Ling +2
We propose an asynchronous, decentralized algorithm for consensus optimization. The algorithm runs over a network in which the agents communicate with their neighbors and perform l…