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Dive into the research topics where Zachary B. Charles is active.

Publication


Featured researches published by Zachary B. Charles.


Journal of Global Optimization | 2018

Exploiting algebraic structure in global optimization and the Belgian chocolate problem

Zachary B. Charles; Nigel Boston

The Belgian chocolate problem involves maximizing a parameter


Mathematics of Computation | 2017

Generating random factored ideals in number fields

Zachary B. Charles


Archive | 2017

Approximate Gradient Coding via Sparse Random Graphs.

Zachary B. Charles; Dimitris S. Papailiopoulos; Jordan S. Ellenberg

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international conference on machine learning | 2018

Stability and Generalization of Learning Algorithms that Converge to Global Optima

Zachary B. Charles; Dimitris S. Papailiopoulos


international conference on machine learning | 2018

DRACO: Robust Distributed Training via Redundant Gradients

Lingjiao Chen; Hongyi Wang; Zachary B. Charles; Dimitris S. Papailiopoulos

δ over a non-convex region of polynomials. In this paper we detail a global optimization method for this problem that outperforms previous such methods by exploiting underlying algebraic structure. Previous work has focused on iterative methods that, due to the complicated non-convex feasible region, may require many iterations or result in non-optimal


Archive | 2017

Subspace Clustering with Missing and Corrupted Data

Zachary B. Charles; Amin Jalali; Rebecca Willett


neural information processing systems | 2018

ATOMO: Communication-efficient Learning via Atomic Sparsification

Hongyi Wang; Scott Sievert; Shengchao Liu; Zachary B. Charles; Dimitris S. Papailiopoulos; Stephen J. Wright

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international symposium on information theory | 2018

Gradient Coding Using the Stochastic Block Model

Zachary B. Charles; Dimitris S. Papailiopoulos


international symposium on circuits and systems | 2018

Distributions of the Number of Solutions to the Network Power Flow Equations

Alisha Zachariah; Zachary B. Charles; Nigel Boston; Bernard C. Lesieutre

δ. By contrast, our method locates the largest known value of


international conference on machine learning | 2018

DRACO: Byzantine-resilient Distributed Training via Redundant Gradients.

Lingjiao Chen; Hongyi Wang; Zachary B. Charles; Dimitris S. Papailiopoulos

Collaboration


Dive into the Zachary B. Charles's collaboration.

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Hongyi Wang

University of Wisconsin-Madison

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Alisha Zachariah

University of Wisconsin-Madison

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Amin Jalali

University of Washington

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Lingjiao Chen

University of Wisconsin-Madison

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Nigel Boston

University of Wisconsin-Madison

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Rebecca Willett

University of Wisconsin-Madison

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Bernard C. Lesieutre

University of Wisconsin-Madison

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Scott Sievert

University of Wisconsin-Madison

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Shengchao Liu

University of Wisconsin-Madison

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