Timezone: »
Distributed algorithms have been playing an increasingly important role in many applications such as machine learning, signal processing, and control. In this work, we provide a fresh perspective to understand, analyze, and design distributed optimization algorithms. Through the lens of multi-rate feedback control, we show that a wide class of distributed algorithms, including popular decentralized/federated schemes, can be viewed as discretizing a certain continuous-time feedback control system, possibly with multiple sampling rates, such as decentralized gradient descent, gradient tracking, and federated averaging. This key observation not only allows us to develop a generic framework to analyze the convergence of the entire algorithm class. More importantly, it also leads to an interesting way of designing new distributed algorithms. We develop the theory behind our framework and provide examples to highlight how the framework can be used in practice.
Author Information
xinwei zhang (University of Minnesota)
Nicola Elia (University of Minnesota)
Mingyi Hong (University of Minnesota)
More from the Same Authors
-
2021 : A Unified Framework to Understand Decentralized and Federated Optimization Algorithms: A Multi-Rate Feedback Control Perspective »
xinwei zhang · Mingyi Hong · Nicola Elia -
2022 : Building Large Machine Learning Models from Small Distributed Models: A Layer Matching Approach »
xinwei zhang · Bingqing Song · Mehrdad Honarkhah · Jie Ding · Mingyi Hong -
2022 : On the Robustness of deep learning-based MRI Reconstruction to image transformations »
jinghan jia · Mingyi Hong · Yimeng Zhang · Mehmet Akcakaya · Sijia Liu -
2023 Poster: VCC: Scaling Transformers to 128K Tokens or More by Prioritizing Important Tokens »
Zhanpeng Zeng · Cole Hawkins · Mingyi Hong · Aston Zhang · Nikolaos Pappas · Vikas Singh · Shuai Zheng -
2023 Poster: Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer Learning »
Yihua Zhang · Yimeng Zhang · Aochuan Chen · jinghan jia · Jiancheng Liu · Gaowen Liu · Mingyi Hong · Shiyu Chang · Sijia Liu -
2023 Poster: A Unified Detection Framework for Inference-Stage Backdoor Defenses »
Xun Xian · Ganghua Wang · Jayanth Srinivasa · Ashish Kundu · Xuan Bi · Mingyi Hong · Jie Ding -
2023 Poster: When Demonstrations meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning »
Siliang Zeng · Chenliang Li · Alfredo Garcia · Mingyi Hong -
2023 Oral: When Demonstrations meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning »
Siliang Zeng · Chenliang Li · Alfredo Garcia · Mingyi Hong -
2022 : Poster Session 1 »
Andrew Lowy · Thomas Bonnier · Yiling Xie · Guy Kornowski · Simon Schug · Seungyub Han · Nicolas Loizou · xinwei zhang · Laurent Condat · Tabea E. Röber · Si Yi Meng · Marco Mondelli · Runlong Zhou · Eshaan Nichani · Adrian Goldwaser · Rudrajit Das · Kayhan Behdin · Atish Agarwala · Mukul Gagrani · Gary Cheng · Tian Li · Haoran Sun · Hossein Taheri · Allen Liu · Siqi Zhang · Dmitrii Avdiukhin · Bradley Brown · Miaolan Xie · Junhyung Lyle Kim · Sharan Vaswani · Xinmeng Huang · Ganesh Ramachandra Kini · Angela Yuan · Weiqiang Zheng · Jiajin Li -
2022 Poster: A Stochastic Linearized Augmented Lagrangian Method for Decentralized Bilevel Optimization »
Songtao Lu · Siliang Zeng · Xiaodong Cui · Mark Squillante · Lior Horesh · Brian Kingsbury · Jia Liu · Mingyi Hong -
2022 Poster: Inducing Equilibria via Incentives: Simultaneous Design-and-Play Ensures Global Convergence »
Boyi Liu · Jiayang Li · Zhuoran Yang · Hoi-To Wai · Mingyi Hong · Yu Nie · Zhaoran Wang -
2022 Poster: Maximum-Likelihood Inverse Reinforcement Learning with Finite-Time Guarantees »
Siliang Zeng · Chenliang Li · Alfredo Garcia · Mingyi Hong -
2022 Poster: Advancing Model Pruning via Bi-level Optimization »
Yihua Zhang · Yuguang Yao · Parikshit Ram · Pu Zhao · Tianlong Chen · Mingyi Hong · Yanzhi Wang · Sijia Liu -
2022 Poster: Distributed Optimization for Overparameterized Problems: Achieving Optimal Dimension Independent Communication Complexity »
Bingqing Song · Ioannis Tsaknakis · Chung-Yiu Yau · Hoi-To Wai · Mingyi Hong -
2021 : Contributed Talk 2: A Unified Framework to Understand Decentralized and Federated Optimization Algorithms: A Multi-Rate Feedback Control Perspective »
xinwei zhang · Mingyi Hong · Nicola Elia -
2021 Poster: STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning »
Prashant Khanduri · PRANAY SHARMA · Haibo Yang · Mingyi Hong · Jia Liu · Ketan Rajawat · Pramod Varshney -
2021 Poster: A Near-Optimal Algorithm for Stochastic Bilevel Optimization via Double-Momentum »
Prashant Khanduri · Siliang Zeng · Mingyi Hong · Hoi-To Wai · Zhaoran Wang · Zhuoran Yang -
2021 Poster: When Expressivity Meets Trainability: Fewer than $n$ Neurons Can Work »
Jiawei Zhang · Yushun Zhang · Mingyi Hong · Ruoyu Sun · Zhi-Quan Luo -
2020 Poster: Finding Second-Order Stationary Points Efficiently in Smooth Nonconvex Linearly Constrained Optimization Problems »
Songtao Lu · Meisam Razaviyayn · Bo Yang · Kejun Huang · Mingyi Hong -
2020 Poster: Understanding Gradient Clipping in Private SGD: A Geometric Perspective »
Xiangyi Chen · Steven Wu · Mingyi Hong -
2020 Poster: Distributed Training with Heterogeneous Data: Bridging Median- and Mean-Based Algorithms »
Xiangyi Chen · Tiancong Chen · Haoran Sun · Steven Wu · Mingyi Hong -
2020 Spotlight: Understanding Gradient Clipping in Private SGD: A Geometric Perspective »
Xiangyi Chen · Steven Wu · Mingyi Hong -
2020 Spotlight: Finding Second-Order Stationary Points Efficiently in Smooth Nonconvex Linearly Constrained Optimization Problems »
Songtao Lu · Meisam Razaviyayn · Bo Yang · Kejun Huang · Mingyi Hong -
2020 Poster: Provably Efficient Neural GTD for Off-Policy Learning »
Hoi-To Wai · Zhuoran Yang · Zhaoran Wang · Mingyi Hong -
2019 : Lunch break and poster »
Felix Sattler · Khaoula El Mekkaoui · Neta Shoham · Cheng Hong · Florian Hartmann · Boyue Li · Daliang Li · Sebastian Caldas Rivera · Jianyu Wang · Kartikeya Bhardwaj · Tribhuvanesh Orekondy · YAN KANG · Dashan Gao · Mingshu Cong · Xin Yao · Songtao Lu · JIAHUAN LUO · Shicong Cen · Peter Kairouz · Yihan Jiang · Tzu Ming Hsu · Aleksei Triastcyn · Yang Liu · Ahmed Khaled · Zhicong Liang · Boi Faltings · Seungwhan Moon · Suyi Li · Tao Fan · Tianchi Huang · Chunyan Miao · Hang Qi · Matthew Brown · Lucas Glass · Junpu Wang · Wei Chen · Radu Marculescu · tomer avidor · Xueyang Wu · Mingyi Hong · Ce Ju · John Rush · Ruixiao Zhang · Youchi ZHOU · Françoise Beaufays · Yingxuan Zhu · Lei Xia -
2019 Poster: Provably Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost »
Zhuoran Yang · Yongxin Chen · Mingyi Hong · Zhaoran Wang -
2019 Poster: Variance Reduced Policy Evaluation with Smooth Function Approximation »
Hoi-To Wai · Mingyi Hong · Zhuoran Yang · Zhaoran Wang · Kexin Tang -
2019 Poster: ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization »
Xiangyi Chen · Sijia Liu · Kaidi Xu · Xingguo Li · Xue Lin · Mingyi Hong · David Cox -
2018 Poster: Multi-Agent Reinforcement Learning via Double Averaging Primal-Dual Optimization »
Hoi-To Wai · Zhuoran Yang · Zhaoran Wang · Mingyi Hong