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Author search results
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- Haibo Yang 0001
Rochester Institute of Technology, NY, USA
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Publication search results
found 26 matches
- 2024
- Haibo Yang, Peiwen Qiu, Prashant Khanduri, Minghong Fang, Jia Liu:
Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation. CoRR abs/2405.02745 (2024) - Tianchen Zhou, Hairi, Haibo Yang, Jia Liu, Tian Tong, Fan Yang, Michinari Momma, Yan Gao:
Finite-Time Convergence and Sample Complexity of Actor-Critic Multi-Objective Reinforcement Learning. CoRR abs/2405.03082 (2024) - 2023
- Haibo Yang, Zhuqing Liu, Jia Liu, Chaosheng Dong, Michinari Momma:
Federated Multi-Objective Learning. NeurIPS 2023 - Haibo Yang, Zhuqing Liu, Jia Liu, Chaosheng Dong, Michinari Momma:
Federated Multi-Objective Learning. CoRR abs/2310.09866 (2023) - 2022
- Prashant Khanduri, Haibo Yang, Mingyi Hong, Jia Liu, Hoi-To Wai, Sijia Liu:
Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach. ICLR 2022 - Haibo Yang, Xin Zhang, Prashant Khanduri, Jia Liu:
Anarchic Federated Learning. ICML 2022: 25331-25363 - Haibo Yang, Peiwen Qiu, Jia Liu, Aylin Yener:
Over-the-Air Federated Learning with Joint Adaptive Computation and Power Control. ISIT 2022: 1259-1264 - Xin Zhang, Minghong Fang, Zhuqing Liu, Haibo Yang, Jia Liu, Zhengyuan Zhu
:
NET-FLEET: achieving linear convergence speedup for fully decentralized federated learning with heterogeneous data. MobiHoc 2022: 71-80 - Haibo Yang, Zhuqing Liu, Xin Zhang, Jia Liu:
SAGDA: Achieving $\mathcal{O}(\epsilon{-2})$ Communication Complexity in Federated Min-Max Learning. NeurIPS 2022 - Haibo Yang, Peiwen Qiu, Jia Liu:
Taming Fat-Tailed ("Heavier-Tailed" with Potentially Infinite Variance) Noise in Federated Learning. NeurIPS 2022 - Jiayu Mao, Haibo Yang, Peiwen Qiu, Jia Liu, Aylin Yener:
CHARLES: Channel-Quality-Adaptive Over-the-Air Federated Learning over Wireless Networks. SPAWC 2022: 1-5 - Haibo Yang, Peiwen Qiu, Jia Liu, Aylin Yener:
Over-the-Air Federated Learning with Joint Adaptive Computation and Power Control. CoRR abs/2205.05867 (2022) - Jiayu Mao, Haibo Yang, Peiwen Qiu, Jia Liu, Aylin Yener:
CHARLES: Channel-Quality-Adaptive Over-the-Air Federated Learning over Wireless Networks. CoRR abs/2205.09330 (2022) - Xin Zhang, Minghong Fang, Zhuqing Liu, Haibo Yang, Jia Liu, Zhengyuan Zhu
:
NET-FLEET: Achieving Linear Convergence Speedup for Fully Decentralized Federated Learning with Heterogeneous Data. CoRR abs/2208.08490 (2022) - Haibo Yang, Zhuqing Liu, Xin Zhang, Jia Liu:
SAGDA: Achieving O(ε-2) Communication Complexity in Federated Min-Max Learning. CoRR abs/2210.00611 (2022) - Haibo Yang, Peiwen Qiu, Jia Liu:
Taming Fat-Tailed ("Heavier-Tailed" with Potentially Infinite Variance) Noise in Federated Learning. CoRR abs/2210.00690 (2022) - 2021
- Haibo Yang, Minghong Fang, Jia Liu:
Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning. ICLR 2021 - Prashant Khanduri, Pranay Sharma, Haibo Yang, Mingyi Hong, Jia Liu, Ketan Rajawat, Pramod K. Varshney:
STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning. NeurIPS 2021: 6050-6061 - Haibo Yang, Jia Liu, Elizabeth S. Bentley:
CFedAvg: Achieving Efficient Communication and Fast Convergence in Non-IID Federated Learning. WiOpt 2021: 113-120 - Haibo Yang, Minghong Fang, Jia Liu:
Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning. CoRR abs/2101.11203 (2021) - Haibo Yang, Jia Liu, Elizabeth S. Bentley:
CFedAvg: Achieving Efficient Communication and Fast Convergence in Non-IID Federated Learning. CoRR abs/2106.07155 (2021) - Prashant Khanduri, Pranay Sharma, Haibo Yang, Mingyi Hong, Jia Liu, Ketan Rajawat, Pramod K. Varshney:
STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning. CoRR abs/2106.10435 (2021) - Haibo Yang, Xin Zhang, Prashant Khanduri, Jia Liu:
Anarchic Federated Learning. CoRR abs/2108.09875 (2021) - 2020
- Haibo Yang, Xin Zhang, Minghong Fang, Jia Liu:
Adaptive Multi-Hierarchical signSGD for Communication-Efficient Distributed Optimization. SPAWC 2020: 1-5 - 2019
- Haibo Yang, Xin Zhang, Minghong Fang, Jia Liu:
Byzantine-Resilient Stochastic Gradient Descent for Distributed Learning: A Lipschitz-Inspired Coordinate-wise Median Approach. CDC 2019: 5832-5837 - Haibo Yang, Xin Zhang, Minghong Fang, Jia Liu:
Byzantine-Resilient Stochastic Gradient Descent for Distributed Learning: A Lipschitz-Inspired Coordinate-wise Median Approach. CoRR abs/1909.04532 (2019)
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