Yi Zhou

According to our database, Yi Zhou authored at least 45 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

MAP: Multi-Human-Value Alignment Palette.

Xinran Wang, Qi Le, Ammar Ahmed, Enmao Diao, Yi Zhou, Nathalie Baracaldo, Jie Ding, Ali Anwar

CoRR, 2024

Mitigating Forgetting in LLM Supervised Fine-Tuning and Preference Learning.

Heshan Devaka Fernando, Han Shen, Parikshit Ram, Yi Zhou, Horst Samulowitz, Nathalie Baracaldo, Tianyi Chen

CoRR, 2024

Turning Generative Models Degenerate: The Power of Data Poisoning Attacks.

Shuli Jiang, Swanand Ravindra Kadhe, Yi Zhou, Farhan Ahmed, Ling Cai, Nathalie Baracaldo

CoRR, 2024

Granite Code Models: A Family of Open Foundation Models for Code Intelligence.

Mayank Mishra, Matt Stallone, Gaoyuan Zhang, Yikang Shen, Aditya Prasad, Adriana Meza Soria, Michele Merler, Parameswaran Selvam, Saptha Surendran, Shivdeep Singh, Manish Sethi, Xuan-Hong Dang, Pengyuan Li, Kun-Lung Wu, Syed Zawad, Andrew Coleman, Matthew White, Mark Lewis, Raju Pavuluri, Yan Koyfman, Boris Lublinsky, Maximilien de Bayser, Ibrahim Abdelaziz, Kinjal Basu, Mayank Agarwal, Yi Zhou, Chris Johnson, Aanchal Goyal, Hima Patel, S. Yousaf Shah, Petros Zerfos, Heiko Ludwig, Asim Munawar, Maxwell Crouse, Pavan Kapanipathi, Shweta Salaria, Bob Calio, Sophia Wen, Seetharami Seelam, Brian Belgodere, Carlos A. Fonseca, Amith Singhee, Nirmit Desai, David D. Cox, Ruchir Puri, Rameswar Panda

CoRR, 2024

Byzantine-Resilient Bilevel Federated Learning.

Momin Abbas, Yi Zhou, Nathalie Baracaldo, Horst Samulowitz, Parikshit Ram, Theodoros Salonidis

Proceedings of the 13th IEEE Sensor Array and Multichannel Signal Processing Workshop, 2024

Towards Collecting Royalties for Copyrighted Data for Generative Models.

Heiko Ludwig, Yi Zhou, Syed Zawad, Yuya Jeremy Ong, Pengyuan Li, Eric Butler, Eelaaf Zahid

Proceedings of the IEEE International Conference on Web Services, 2024

Enhancing In-context Learning via Linear Probe Calibration.

Momin Abbas, Yi Zhou, Parikshit Ram, Nathalie Baracaldo, Horst Samulowitz, Theodoros Salonidis, Tianyi Chen

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Effective Data Distillation for Tabular Datasets (Student Abstract).

Inwon Kang, Parikshit Ram, Yi Zhou, Horst Samulowitz, Oshani Seneviratne

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Graph Topology Invariant Gradient and Sampling Complexity for Decentralized and Stochastic Optimization.

Guanghui Lan, Yuyuan Ouyang, Yi Zhou

SIAM J. Optim., September, 2023

Forcing Generative Models to Degenerate Ones: The Power of Data Poisoning Attacks.

Shuli Jiang, Swanand Ravindra Kadhe, Yi Zhou, Ling Cai, Nathalie Baracaldo

CoRR, 2023

Privacy-Preserving Federated Learning over Vertically and Horizontally Partitioned Data for Financial Anomaly Detection.

Swanand Ravindra Kadhe, Heiko Ludwig, Nathalie Baracaldo, Alan King, Yi Zhou, Keith Houck, Ambrish Rawat, Mark Purcell, Naoise Holohan, Mikio Takeuchi, Ryo Kawahara, Nir Drucker, Hayim Shaul, Eyal Kushnir, Omri Soceanu

CoRR, 2023

Benchmarking the Effect of Poisoning Defenses on the Security and Bias of Deep Learning Models.

Nathalie Baracaldo, Farhan Ahmed, Kevin Eykholt, Yi Zhou, Shriti Priya, Taesung Lee, Swanand Kadhe, Mike Tan, Sridevi Polavaram, Sterling Suggs, Yuyang Gao, David Slater

Proceedings of the 2023 IEEE Security and Privacy Workshops (SPW), 2023

LESS-VFL: Communication-Efficient Feature Selection for Vertical Federated Learning.

Timothy Castiglia, Yi Zhou, Shiqiang Wang, Swanand Kadhe, Nathalie Baracaldo, Stacy Patterson

Proceedings of the International Conference on Machine Learning, 2023

Single-shot General Hyper-parameter Optimization for Federated Learning.

Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz, Heiko Ludwig

Proceedings of the Eleventh International Conference on Learning Representations, 2023

HDFL: A Heterogeneity and Client Dropout-Aware Federated Learning Framework.

Syed Zawad, Ali Anwar, Yi Zhou, Nathalie Baracaldo, Feng Yan

Proceedings of the 23rd IEEE/ACM International Symposium on Cluster, 2023

2022

Federated XGBoost on Sample-Wise Non-IID Data.

Katelinh Jones, Yuya Jeremy Ong, Yi Zhou, Nathalie Baracaldo

CoRR, 2022

Single-shot Hyper-parameter Optimization for Federated Learning: A General Algorithm & Analysis.

Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz, Heiko Ludwig

CoRR, 2022

Heterogeneity-Aware Adaptive Federated Learning Scheduling.

Jingoo Han, Ahmad Faraz Khan, Syed Zawad, Ali Anwar, Nathalie Baracaldo, Yi Zhou, Feng Yan, Ali Raza Butt

Proceedings of the IEEE International Conference on Big Data, 2022

DeTrust-FL: Privacy-Preserving Federated Learning in Decentralized Trust Setting.

Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, Swanand Kadhe, Heiko Ludwig

Proceedings of the IEEE 15th International Conference on Cloud Computing, 2022

TIFF: Tokenized Incentive for Federated Learning.

Jingoo Han, Ahmad Faraz Khan, Syed Zawad, Ali Anwar, Nathalie Baracaldo, Yi Zhou, Feng Yan, Ali Raza Butt

Proceedings of the IEEE 15th International Conference on Cloud Computing, 2022

Privacy-Preserving Vertical Federated Learning.

Runhua Xu, Nathalie Baracaldo, Yi Zhou, Annie Abay, Ali Anwar

Proceedings of the Federated Learning, 2022

Federated Learning for Collaborative Financial Crimes Detection.

Toyotaro Suzumura, Yi Zhou, Ryo Kawahara, Nathalie Baracaldo, Heiko Ludwig

Proceedings of the Federated Learning, 2022

Tree-Based Models for Federated Learning Systems.

Yuya Jeremy Ong, Nathalie Baracaldo, Yi Zhou

Proceedings of the Federated Learning, 2022

Federated Learning and Fairness.

Annie Abay, Yi Zhou, Nathalie Baracaldo, Heiko Ludwig

Proceedings of the Federated Learning, 2022

Dealing with Byzantine Threats to Neural Networks.

Yi Zhou, Nathalie Baracaldo, Ali Anwar, Kamala Varma

Proceedings of the Federated Learning, 2022

2021

Asynchronous Decentralized Accelerated Stochastic Gradient Descent.

Guanghui Lan, Yi Zhou

IEEE J. Sel. Areas Inf. Theory, 2021

FLoRA: Single-shot Hyper-parameter Optimization for Federated Learning.

Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz, Heiko Ludwig

CoRR, 2021

FedV: Privacy-Preserving Federated Learning over Vertically Partitioned Data.

Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, James Joshi, Heiko Ludwig

Proceedings of the AISec@CCS 2021: Proceedings of the 14th ACM Workshop on Artificial Intelligence and Security, 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 Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

LEGATO: A LayerwisE Gradient AggregaTiOn Algorithm for Mitigating Byzantine Attacks in Federated Learning.

Kamala Varma, Yi Zhou, Nathalie Baracaldo, Ali Anwar

Proceedings of the 14th IEEE International Conference on Cloud Computing, 2021

2020

Communication-efficient algorithms for decentralized and stochastic optimization.

Guanghui Lan, Soomin Lee, Yi Zhou

Math. Program., 2020

Adaptive Histogram-Based Gradient Boosted Trees for Federated Learning.

Yuya Jeremy Ong, Yi Zhou, Nathalie Baracaldo, Heiko Ludwig

CoRR, 2020

Mitigating Bias in Federated Learning.

Annie Abay, Yi Zhou, Nathalie Baracaldo, Shashank Rajamoni, Ebube Chuba, Heiko Ludwig

CoRR, 2020

IBM Federated Learning: an Enterprise Framework White Paper V0.1.

Heiko Ludwig, Nathalie Baracaldo, Gegi Thomas, Yi Zhou, Ali Anwar, Shashank Rajamoni, Yuya Jeremy Ong, Jayaram Radhakrishnan, Ashish Verma, Mathieu Sinn, Mark Purcell, Ambrish Rawat, Tran Ngoc Minh, Naoise Holohan, Supriyo Chakraborty, Shalisha Witherspoon, Dean Steuer, Laura Wynter, Hifaz Hassan, Sean Laguna, Mikhail Yurochkin, Mayank Agarwal, Ebube Chuba, Annie Abay

CoRR, 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 HPDC '20: The 29th International Symposium on High-Performance Parallel and Distributed Computing, 2020

2019

A Hybrid Approach to Privacy-Preserving Federated Learning - (Extended Abstract).

Stacey Truex, Nathalie Baracaldo, Ali Anwar, Thomas Steinke, Heiko Ludwig, Rui Zhang, Yi Zhou

Inform. Spektrum, 2019

Towards Federated Graph Learning for Collaborative Financial Crimes Detection.

Toyotaro Suzumura, Yi Zhou, Nathalie Barcardo, Guangnan Ye, Keith Houck, Ryo Kawahara, Ali Anwar, Lucia Larise Stavarache, Daniel Klyashtorny, Heiko Ludwig, Kumar Bhaskaran

CoRR, 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

Proceedings of the 2019 USENIX Conference on Operational Machine Learning, 2019

A unified variance-reduced accelerated gradient method for convex optimization.

Guanghui Lan, Zhize Li, Yi Zhou

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 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, 2019

A Hybrid Approach to Privacy-Preserving Federated Learning.

Stacey Truex, Nathalie Baracaldo, Ali Anwar, Thomas Steinke, Heiko Ludwig, Rui Zhang, Yi Zhou

Proceedings of the 12th ACM Workshop on Artificial Intelligence and Security, 2019

2018

Random Gradient Extrapolation for Distributed and Stochastic Optimization.

Guanghui Lan, Yi Zhou

SIAM J. Optim., 2018

An optimal randomized incremental gradient method.

Guanghui Lan, Yi Zhou

Math. Program., 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, 2017

2016

Conditional Gradient Sliding for Convex Optimization.

Guanghui Lan, Yi Zhou

SIAM J. Optim., 2016