Search Results for author: Zhengyuan Zhu

Found 10 papers, 0 papers with code

NET-FLEET: Achieving Linear Convergence Speedup for Fully Decentralized Federated Learning with Heterogeneous Data

no code implementations17 Aug 2022 Xin Zhang, Minghong Fang, Zhuqing Liu, Haibo Yang, Jia Liu, Zhengyuan Zhu

Moreover, whether or not the linear speedup for convergence is achievable under fully decentralized FL with data heterogeneity remains an open question.

Federated Learning

Taming Communication and Sample Complexities in Decentralized Policy Evaluation for Cooperative Multi-Agent Reinforcement Learning

no code implementations NeurIPS 2021 Xin Zhang, Zhuqing Liu, Jia Liu, Zhengyuan Zhu, Songtao Lu

To our knowledge, this paper is the first work that achieves both $\mathcal{O}(\epsilon^{-2})$ sample complexity and $\mathcal{O}(\epsilon^{-2})$ communication complexity in decentralized policy evaluation for cooperative MARL.

Multi-agent Reinforcement Learning reinforcement-learning +1

GT-STORM: Taming Sample, Communication, and Memory Complexities in Decentralized Non-Convex Learning

no code implementations4 May 2021 Xin Zhang, Jia Liu, Zhengyuan Zhu, Elizabeth S. Bentley

Decentralized nonconvex optimization has received increasing attention in recent years in machine learning due to its advantages in system robustness, data privacy, and implementation simplicity.

A Dashboard for Mitigating the COVID-19 Misinfodemic

no code implementations EACL 2021 Zhengyuan Zhu, Kevin Meng, Josue Caraballo, Israa Jaradat, Xiao Shi, Zeyu Zhang, Farahnaz Akrami, Haojin Liao, Fatma Arslan, Damian Jimenez, Mohanmmed Samiul Saeef, Paras Pathak, Chengkai Li

This paper describes the current milestones achieved in our ongoing project that aims to understand the surveillance of, impact of and intervention on COVID-19 misinfodemic on Twitter.


Private and Communication-Efficient Edge Learning: A Sparse Differential Gaussian-Masking Distributed SGD Approach

no code implementations12 Jan 2020 Xin Zhang, Minghong Fang, Jia Liu, Zhengyuan Zhu

In this paper, we consider the problem of jointly improving data privacy and communication efficiency of distributed edge learning, both of which are critical performance metrics in wireless edge network computing.

Spatial Heterogeneity Automatic Detection and Estimation

no code implementations5 Jun 2019 Xin Wang, Zhengyuan Zhu, Hao Helen Zhang

Spatial regression is widely used for modeling the relationship between a dependent variable and explanatory covariates.


Distributed Linear Model Clustering over Networks: A Tree-Based Fused-Lasso ADMM Approach

no code implementations28 May 2019 Xin Zhang, Jia Liu, Zhengyuan Zhu

In this work, we consider to improve the model estimation efficiency by aggregating the neighbors' information as well as identify the subgroup membership for each node in the network.

Regression-Enhanced Random Forests

no code implementations23 Apr 2019 Haozhe Zhang, Dan Nettleton, Zhengyuan Zhu

Random forest (RF) methodology is one of the most popular machine learning techniques for prediction problems.

BIG-bench Machine Learning

Spatial CUSUM for Signal Region Detection

no code implementations5 Apr 2019 Xin Zhang, Zhengyuan Zhu

We develop theoretical properties of the method which indicates that asymptotically SCUSUM can reach high classification accuracy.


Taming Convergence for Asynchronous Stochastic Gradient Descent with Unbounded Delay in Non-Convex Learning

no code implementations24 May 2018 Xin Zhang, Jia Liu, Zhengyuan Zhu

Understanding the convergence performance of asynchronous stochastic gradient descent method (Async-SGD) has received increasing attention in recent years due to their foundational role in machine learning.

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