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portfolio

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publications

Recognizing Actions during Tactile Manipulations through Force Sensing

G. Subramani, D. Rakita, H. Wang, J. Black, M. Zinn, M. Gleicher, IROS 2017, [link]

Draco: Robust Distributed Training against Adversaries

L. Chen, H. Wang, D. Papailiopoulos, SysML 2018, [link]

DRACO: Robust Distributed Training via Redundant Gradients

L. Chen, H. Wang, Z. Charles, D. Papailiopoulos, ICML 2018, [link]

ATOMO: Communication-efficient Learning via Atomic Sparsification

H. Wang*, S. Sievert*, Z. Charles, S. Wright, D. Papailiopoulos, NeurIPS 2018, [link]

The Effect of Network Width on the Performance of Large-batch Training

L. Chen, H. Wang, J. Zhao, D. Papailiopoulos, P. Koutris, NeurIPS 2018, [link]

ErasureHead: Distributed Gradient Descent without Delays Using Approximate Gradient Coding

H. Wang, Z. Charles, D. Papailiopoulos [arXiv]

Demonstration of Nimbus: Model-based Pricing for Machine Learning in a Data Marketplace

L. Chen, H. Wang, L. Chen, P. Koutris, A. Kumar, ACM SIGMOD 2019 demo track, [link]

Convergence and Runtime of Approximate Gradient Coded Gradient Descent

H. Wang, Z. Charles, D. Papailiopoulos, ICML 2019 CodML Workshop, [link]

DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation

S. Rajput*, H. Wang*, Z. Charles, D. Papailiopoulos, NeurIPS 2019, [link]

Federated Learning with Matched Averaging

H. Wang, M. Yurochkin, Y. Sun, D. Papailiopoulos, Y. Khazaeni, ICLR 2020, ($\color{red}{\text{Oral}}$, Acceptance rate: $\color{red}{1.85\%}$) [link][blog][talk]

Attack of the Tails: Yes, You Really Can Backdoor Federated Learning

H. Wang, K. Sreenivasan, S. Rajput, H. Vishwakarma, S. Agarwal, J. Sohn, K. Lee, D. Papailiopoulos, NeurIPS 2020, [link]

FedML: A Research Library and Benchmark for Federated Machine Learning

C. He, S. Li, J. So, M. Zhang, H. Wang, X. Wang, P. Vepakomma, A. Singh, H. Qiu, L. Shen, P. Zhao, Y. Kang, Y. Liu, R. Raskar, Q. Yang, M. Annavaram, S. Avestimehr, NeurIPS 2020 SpicyFL workshop, ($\color{red}{\text{Best Paper Award}}$) [arXiv]

Accordion: Adaptive Gradient Communication via Critical Learning Regime Identification

S. Agarwal, H. Wang, K. Lee, S. Venkataraman, D. Papailiopoulos, MLSys 2021, [arXiv]

PUFFERFISH: Communication-efficient Models at No Extra Cost

H. Wang, S. Agarwal, D. Papailiopoulos, MLSys 2021

talks

Draco: Robust Distributed Training against Adversaries

DRACO:Robust Distributed Training via Redundant Gradients

DRACO: Byzantine-resilient Distributed Training via Redundant Gradients

teaching

Teaching experience 1

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Teaching experience 2

This is a description of a teaching experience. You can use markdown like any other post.