Cong Xie

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University of Illinois at Urbana-Champaign

Chimbuko: A Workflow-Level Scalable Performance Trace Analysis Tool

Because of the limits input/output systems currently impose on high-perf...
08/31/2020 ∙ by Sungsoo Ha, et al. ∙ 0 ∙ share

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SMAP: A Joint Dimensionality Reduction Scheme for Secure Multi-Party Visualization

Nowadays, as data becomes increasingly complex and distributed, data ana...
07/30/2020 ∙ by Jiazhi Xia, et al. ∙ 0 ∙ share

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CSER: Communication-efficient SGD with Error Reset

The scalability of Distributed Stochastic Gradient Descent (SGD) is toda...
07/26/2020 ∙ by Cong Xie, et al. ∙ 2 ∙ share

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Local AdaAlter: Communication-Efficient Stochastic Gradient Descent with Adaptive Learning Rates

Recent years have witnessed the growth of large-scale distributed machin...
11/20/2019 ∙ by Cong Xie, et al. ∙ 0 ∙ share

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Zeno++: robust asynchronous SGD with arbitrary number of Byzantine workers

We propose Zeno++, a new robust asynchronous synchronous Stochastic Grad...
03/17/2019 ∙ by Cong Xie, et al. ∙ 0 ∙ share

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SLSGD: Secure and Efficient Distributed On-device Machine Learning

We consider distributed on-device learning with limited communication an...
03/16/2019 ∙ by Cong Xie, et al. ∙ 0 ∙ share

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Practical Distributed Learning: Secure Machine Learning with Communication-Efficient Local Updates

Federated learning on edge devices poses new challenges arising from wor...
03/16/2019 ∙ by Cong Xie, et al. ∙ 0 ∙ share

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Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product Manipulation

Recently, new defense techniques have been developed to tolerate Byzanti...
03/10/2019 ∙ by Cong Xie, et al. ∙ 0 ∙ share

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Asynchronous Federated Optimization

Federated learning enables training on a massive number of edge devices....
03/10/2019 ∙ by Cong Xie, et al. ∙ 0 ∙ share

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Zeno: Byzantine-suspicious stochastic gradient descent

We propose Zeno, a new robust aggregation rule, for distributed synchron...
05/25/2018 ∙ by Cong Xie, et al. ∙ 0 ∙ share

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Phocas: dimensional Byzantine-resilient stochastic gradient descent

We propose a novel robust aggregation rule for distributed synchronous S...
05/23/2018 ∙ by Cong Xie, et al. ∙ 0 ∙ share

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Generalized Byzantine-tolerant SGD

We propose three new robust aggregation rules for distributed synchronou...
02/27/2018 ∙ by Cong Xie, et al. ∙ 0 ∙ share

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Attack RMSE Leaderboard: An Introduction and Case Study

In this manuscript, we briefly introduce several tricks to climb the lea...
02/14/2018 ∙ by Cong Xie, et al. ∙ 0 ∙ share

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Wishart Mechanism for Differentially Private Principal Components Analysis

We propose a new input perturbation mechanism for publishing a covarianc...
11/18/2015 ∙ by Wuxuan Jiang, et al. ∙ 0 ∙ share

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A Scalable and Extensible Framework for Superposition-Structured Models

In many learning tasks, structural models usually lead to better interpr...
09/08/2015 ∙ by Shenjian Zhao, et al. ∙ 0 ∙ share

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Cong Xie

Featured Co-authors

Lei Zhang

Wei Chen

Wei Xu

Yang Chen

Mu Li

Oluwasanmi Koyejo

Zhihua Zhang

Shuai Zheng

Li Tang

Indranil Gupta

Sanmi Koyejo

Chimbuko: A Workflow-Level Scalable Performance Trace Analysis Tool

SMAP: A Joint Dimensionality Reduction Scheme for Secure Multi-Party Visualization

CSER: Communication-efficient SGD with Error Reset

Local AdaAlter: Communication-Efficient Stochastic Gradient Descent with Adaptive Learning Rates

Zeno++: robust asynchronous SGD with arbitrary number of Byzantine workers

SLSGD: Secure and Efficient Distributed On-device Machine Learning

Practical Distributed Learning: Secure Machine Learning with Communication-Efficient Local Updates

Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product Manipulation

Asynchronous Federated Optimization

Zeno: Byzantine-suspicious stochastic gradient descent

Phocas: dimensional Byzantine-resilient stochastic gradient descent

Generalized Byzantine-tolerant SGD

Attack RMSE Leaderboard: An Introduction and Case Study

Wishart Mechanism for Differentially Private Principal Components Analysis

A Scalable and Extensible Framework for Superposition-Structured Models