Yi Zhou  Yi Zhou photo         

contact information

Research Staff Member
Almaden Research Center, San Jose, CA, USA
  +1dash4089271570

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Professional Associations

Professional Associations:  INFORMS  |  INFORMS Optimization Society  |  Society for Industrial and Applied Mathematics  |  Society of Women Engineers


2023

Single-shot General Hyper-parameter Optimization for Federated Learning
Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz, Heiko Ludwig
International Conference on Learning Representations, 2023


2022

Heterogeneity-Aware Adaptive Federated Learning Scheduling
Jingoo Han, Ahmad Faraz Khan, Syed Zawad, Ali Anwar, Nathalie Baracaldo Angel, Yi Zhou, Feng Yan, Ali R Butt
2022 IEEE International Conference on Big Data (Big Data), pp. 911--920

Tiff: Tokenized incentive for federated learning
Jingoo Han, Ahmad Faraz Khan, Syed Zawad, Ali Anwar, Nathalie Baracaldo Angel, Yi Zhou, Feng Yan, Ali R Butt
2022 IEEE 15th International Conference on Cloud Computing (CLOUD), pp. 407--416

Benchmarking the Effect of Poisoning Defenses on the Security and Bias of the Final Model
Nathalie Baracaldo, Kevin Eykholt, Farhan Ahmed, Yi Zhou, Shriti Priya, Taesung Lee, Swanand Kadhe, Yusong Tan, Sridevi Polavaram, Sterling Suggs, others
Workshop on Trustworthy and Socially Responsible Machine Learning, NeurIPS 2022

DeTrust-FL: Privacy-Preserving Federated Learning in Decentralized Trust Setting
Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, Swanand Kadhe, Heiko Ludwig
2022 IEEE 15th International Conference on Cloud Computing (CLOUD), pp. 417--426


2021

FLoRA: Single-shot Hyper-parameter Optimization for Federated Learning
Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz, Heiko Ludwig
arXiv preprint arXiv:2112.08524, 2021

LEGATO: A LayerwisE Gradient AggregaTiOn Algorithm for Mitigating Byzantine Attacks in Federated Learning
Kamala Varma, Yi Zhou, Nathalie Baracaldo, Ali Anwar
2021 IEEE 14th International Conference on Cloud Computing (CLOUD), pp. 272--277

FedV: Privacy-Preserving Federated Learning over Vertically Partitioned Data
Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, James Joshi, Heiko Ludwig
Proceedings of the 14th ACM Workshop on Artificial Intelligence and Security, pp. 181--192, 2021

Curse or redemption? how data heterogeneity affects the robustness of federated learning
Syed Zawad, Ahsan Ali, Pin-Yu Chen, Ali Anwar, Yi Zhou, Nathalie Baracaldo, Yuan Tian, Feng Yan
Proceedings of the AAAI Conference on Artificial Intelligence, pp. 10807--10814, 2021

Asynchronous decentralized accelerated stochastic gradient descent
Guanghui Lan, Yi Zhou
IEEE Journal on Selected Areas in Information Theory 2(2), 802--811, IEEE, 2021

Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning
S. Zawad, A. Ali, P. Chen, A. Anwar, Y. Zhou, N. Baracaldo, Y. Tian and F. Yan
The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), 2021


2020

Adaptive Histogram-Based Gradient Boosted Trees for Federated Learning
Yuya Jeremy Ong, Yi Zhou, Nathalie Baracaldo, Heiko Ludwig
arXiv preprint arXiv:2012.06670, 2020

Mitigating Bias in Federated Learning
Annie Abay, Yi Zhou, Nathalie Baracaldo, Shashank Rajamoni, Ebube Chuba, Heiko Ludwig
arXiv preprint arXiv:2012.02447, 2020

Tifl: A tier-based federated learning system
Zheng Chai, Ahsan Ali, Syed Zawad, Stacey Truex, Ali Anwar, Nathalie Baracaldo, Yi Zhou, Heiko Ludwig, Feng Yan, Yue Cheng
Proceedings of the 29th International Symposium on High-Performance Parallel and Distributed Computing, pp. 125--136, 2020

Graph topology invariant gradient and sampling complexity for decentralized and stochastic optimization
G. Lan, Y. Ouyang, and Y. Zhou
arXiv preprint arXiv:2101.00143 , 2020

IBM Federated Learning: an Enterprise Framework White Paper V0. 1
Heiko Ludwig, Nathalie Baracaldo, Gegi Thomas, Yi Zhou, Ali Anwar, Shashank Rajamoni, Yuya Ong, Jayaram Radhakrishnan, Ashish Verma, Mathieu Sinn, Mark Purcell, Ambrish Rawat, Tran Minh, Naoise Holohan, Supriyo Chakraborty, Shalisha Whitherspoon, Dean Steuer, Laura Wynter, Hifaz Hassan, Sean Laguna, Mikhail Yurochkin, Mayank Agarwal, Ebube Chuba, Annie Abay
arXiv:2007.10987 , 2020

Communication-efficient Algorithms for Decentralized and Stochastic Optimization
G. Lan, S. Lee and Y. Zhou
Mathematical Programming 180.1 (2020): 237-284.


2019

Towards federated graph learning for collaborative financial crimes detection
Toyotaro Suzumura, Yi Zhou, Natahalie Baracaldo, Guangnan Ye, Keith Houck, Ryo Kawahara, Ali Anwar, Lucia Larise Stavarache, Yuji Watanabe, Pablo Loyola, others
arXiv preprint arXiv:1909.12946, 2019

Hybridalpha: An efficient approach for privacy-preserving federated learning
Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, Heiko Ludwig
Proceedings of the 12th ACM Workshop on Artificial Intelligence and Security, pp. 13--23, 2019

A hybrid approach to privacy-preserving federated learning
S. Truex, N. Baracaldo, A. Anwar, T. Steinke, H. Ludwig, R. Zhang, Y. Zhou
InProceedings of the 12th ACM Workshop on Artificial Intelligence and Security, 2019

A unified variance-reduced accelerated gradient method for convex optimization
Guanghui Lan, Zhize Li, and Yi Zhou
33rd Conference on Neural Information Processing Systems (NeurIPS 2019)

Towards Taming the Resource and Data Heterogeneity in Federated Learning
Zheng Chai, Hannan Fayyaz, Zeshan Fayyaz, Ali Anwar, Yi Zhou, Nathalie Baracaldo, Heiko Ludwig, Yue Cheng
2019 USENIX Conference on Operational Machine Learning (USENIX OpML'19)


2018

Random Gradient Extrapolation for Distributed and Stochastic Optimization
Lan, Guanghui and Zhou, Yi
SIAM Journal on Optimization 28(4), 2753--2782, SIAM, 2018

An Optimal Randomized Incremental Gradient Method
Lan, Guanghui and Zhou, Yi
Mathematical programming 171(1-2), 167--215, Springer, 2018


2017

Conditional Accelerated Lazy Stochastic Gradient Descent
Guanghui Lan, Sebastian Pokutta, Yi Zhou, Daniel Zink
Proceedings of the 34th International Conference on Machine Learning, pp. 1965--1974, PMLR, 2017


2016

Conditional Gradient Sliding for Convex Optimization
Lan, Guanghui, and Yi Zhou.
SIAM Journal on Optimization 26(2), 1379--1409, SIAM, 2016