26 citations · 52 across the 6 of their papers we have counts for
12 papers · 1 filter
A Communication-Efficient Decentralized Newton's Method with Provably Faster Convergence
Huikang Liu, Jiaojiao Zhang, Anthony Man-Cho So +1
In this paper, we consider a strongly convex finite-sum minimization problem over a decentralized network and propose a communication-efficient decentralized Newton's method for so…
Variance-Reduced Stochastic Quasi-Newton Methods for Decentralized Learning: Part II
Jiaojiao Zhang, Huikang Liu, Anthony Man-Cho So +1
In Part I of this work, we have proposed a general framework of decentralized stochastic quasi-Newton methods, which converge linearly to the optimal solution under the assumption…
Stochastic Alternating Direction Method of Multipliers for Byzantine-Robust Distributed Learning
Feng Lin, Weiyu Li, Qing Ling
This paper aims to solve a distributed learning problem under Byzantine attacks. In the underlying distributed system, a number of unknown but malicious workers (termed as Byzantin…
A Newton Tracking Algorithm with Exact Linear Convergence Rate for Decentralized Consensus Optimization
Jiaojiao Zhang, Qing Ling, Anthony Man-Cho So
This paper considers the decentralized consensus optimization problem defined over a network where each node holds a second-order differentiable local objective function. Our goal…
Byzantine-Robust Decentralized Stochastic Optimization over Static and Time-Varying Networks
Jie Peng, Weiyu Li, Qing Ling
In this paper, we consider the Byzantine-robust stochastic optimization problem defined over decentralized static and time-varying networks, where the agents collaboratively minimi…
Can Primal Methods Outperform Primal-dual Methods in Decentralized Dynamic Optimization?
Kun Yuan, Wei Xu, Qing Ling
In this paper, we consider the decentralized dynamic optimization problem defined over a multi-agent network. Each agent possesses a time-varying local objective function, and all…