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ORCIDAmir Salman Avestimehr
Salman Avestimehr
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- affiliation: University of Southern California, Los Angeles, USA
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2020 – today
- 2024
[j92]Baturalp Buyukates
, Jinhyun So, Hessam Mahdavifar, Salman Avestimehr:
LightVeriFL: A Lightweight and Verifiable Secure Aggregation for Federated Learning. IEEE J. Sel. Areas Inf. Theory 5: 285-301 (2024)- [j91]Baturalp Buyukates, Jinhyun So, Hessam Mahdavifar, Salman Avestimehr:
Erratum to "LightVeriFL: A Lightweight and Verifiable Secure Aggregation for Federated Learning". IEEE J. Sel. Areas Inf. Theory 5: 570-571 (2024) - [j90]Onat Dalmaz, Muhammad Usama Mirza, Gökberk Elmas, Muzaffer Özbey, Salman Ul Hassan Dar, Emir Ceyani, Kader Karli Oguz, Salman Avestimehr, Tolga Çukur:
One model to unite them all: Personalized federated learning of multi-contrast MRI synthesis. Medical Image Anal. 94: 103121 (2024) - [j89]Hamza Saleem, Amir Ziashahabi, Muhammad Naveed, Salman Avestimehr:
Hawk: Accurate and Fast Privacy-Preserving Machine Learning Using Secure Lookup Table Computation. Proc. Priv. Enhancing Technol. 2024(3): 42-58 (2024) - [j88]Tingting Tang, Yue Niu, Salman Avestimehr, Murali Annavaram:
Edge Private Graph Neural Networks with Singular Value Perturbation. Proc. Priv. Enhancing Technol. 2024(3): 391-406 (2024) - [c173]Tuo Zhang, Jinyue Yuan, Salman Avestimehr:
Revisiting OPRO: The Limitations of Small-Scale LLMs as Optimizers. ACL (Findings) 2024: 1727-1735 - [c172]Yavuz Faruk Bakman, Duygu Nur Yaldiz, Baturalp Buyukates, Chenyang Tao, Dimitrios Dimitriadis, Salman Avestimehr:
MARS: Meaning-Aware Response Scoring for Uncertainty Estimation in Generative LLMs. ACL (1) 2024: 7752-7767 - [c171]Yavuz Faruk Bakman, Duygu Nur Yaldiz, Yahya H. Ezzeldin, Salman Avestimehr:
Federated Orthogonal Training: Mitigating Global Catastrophic Forgetting in Continual Federated Learning. ICLR 2024 - [c170]Shanshan Han, Baturalp Buyukates, Zijian Hu, Han Jin, Weizhao Jin, Lichao Sun, Xiaoyang Wang, Wenxuan Wu, Chulin Xie, Yuhang Yao, Kai Zhang, Qifan Zhang, Yuhui Zhang, Carlee Joe-Wong, Salman Avestimehr, Chaoyang He:
FedSecurity: A Benchmark for Attacks and Defenses in Federated Learning and Federated LLMs. KDD 2024: 5070-5081 - [c169]Junyuan Hong, Carl Yang, Zhuangdi Zhu, Zheng Xu, Nathalie Baracaldo, Neil Shah, Salman Avestimehr, Jiayu Zhou:
FedKDD: International Joint Workshop on Federated Learning for Data Mining and Graph Analytics. KDD 2024: 6718-6719 - [c168]Lei Gao, Yue Niu, Tingting Tang, Salman Avestimehr, Murali Annavaram:
Ethos: Rectifying Language Models in Orthogonal Parameter Space. NAACL-HLT (Findings) 2024: 2054-2068 - [i202]Yavuz Faruk Bakman, Duygu Nur Yaldiz, Baturalp Buyukates, Chenyang Tao, Dimitrios Dimitriadis, Salman Avestimehr:
MARS: Meaning-Aware Response Scoring for Uncertainty Estimation in Generative LLMs. CoRR abs/2402.11756 (2024) - [i201]Yue Niu, Saurav Prakash, Salman Avestimehr:
ATP: Enabling Fast LLM Serving via Attention on Top Principal Keys. CoRR abs/2403.02352 (2024) - [i200]Lei Gao, Yue Niu, Tingting Tang, Salman Avestimehr, Murali Annavaram:
Ethos: Rectifying Language Models in Orthogonal Parameter Space. CoRR abs/2403.08994 (2024) - [i199]Tingting Tang, Yue Niu, Salman Avestimehr, Murali Annavaram:
Edge Private Graph Neural Networks with Singular Value Perturbation. CoRR abs/2403.10995 (2024) - [i198]Hamza Saleem, Amir Ziashahabi, Muhammad Naveed, Salman Avestimehr:
Hawk: Accurate and Fast Privacy-Preserving Machine Learning Using Secure Lookup Table Computation. CoRR abs/2403.17296 (2024) - [i197]Joshua C. Zhao, Saurabh Bagchi, Salman Avestimehr, Kevin S. Chan, Somali Chaterji, Dimitris Dimitriadis, Jiacheng Li, Ninghui Li, Arash Nourian, Holger R. Roth:
Federated Learning Privacy: Attacks, Defenses, Applications, and Policy Landscape - A Survey. CoRR abs/2405.03636 (2024) - [i196]Tuo Zhang, Jinyue Yuan, Salman Avestimehr:
Revisiting OPRO: The Limitations of Small-Scale LLMs as Optimizers. CoRR abs/2405.10276 (2024) - [i195]Mengwei Yang, Ismat Jarin, Baturalp Buyukates, Salman Avestimehr, Athina Markopoulou:
Maverick-Aware Shapley Valuation for Client Selection in Federated Learning. CoRR abs/2405.12590 (2024) - [i194]Tuo Zhang, Tiantian Feng, Yibin Ni, Mengqin Cao, Ruying Liu, Katharine Butler, Yanjun Weng, Mi Zhang, Shrikanth S. Narayanan, Salman Avestimehr:
Creating a Lens of Chinese Culture: A Multimodal Dataset for Chinese Pun Rebus Art Understanding. CoRR abs/2406.10318 (2024) - [i193]Duygu Nur Yaldiz, Yavuz Faruk Bakman, Baturalp Buyukates, Chenyang Tao, Anil Ramakrishna, Dimitrios Dimitriadis, Salman Avestimehr:
Do Not Design, Learn: A Trainable Scoring Function for Uncertainty Estimation in Generative LLMs. CoRR abs/2406.11278 (2024) - [i192]Sunwoo Lee, Tuo Zhang, Saurav Prakash, Yue Niu, Salman Avestimehr:
Embracing Federated Learning: Enabling Weak Client Participation via Partial Model Training. CoRR abs/2406.15125 (2024) - [i191]Erum Mushtaq, Duygu Nur Yaldiz, Yavuz Faruk Bakman, Jie Ding, Chenyang Tao, Dimitrios Dimitriadis, Salman Avestimehr:
CroMo-Mixup: Augmenting Cross-Model Representations for Continual Self-Supervised Learning. CoRR abs/2407.12188 (2024) - [i190]Asal Mehradfar, Xuzhe Zhao, Yue Niu, Sara Babakniya, Mahdi Alesheikh, Hamidreza Aghasi, Salman Avestimehr:
AICircuit: A Multi-Level Dataset and Benchmark for AI-Driven Analog Integrated Circuit Design. CoRR abs/2407.18272 (2024) - [i189]Yuhang Yao, Han Jin, Alay Dilipbhai Shah, Shanshan Han, Zijian Hu, Yide Ran, Dimitris Stripelis, Zhaozhuo Xu, Salman Avestimehr, Chaoyang He:
ScaleLLM: A Resource-Frugal LLM Serving Framework by Optimizing End-to-End Efficiency. CoRR abs/2408.00008 (2024) - 2023
- [j87]Sunwoo Lee, Anit Kumar Sahu, Chaoyang He, Salman Avestimehr:
Partial model averaging in Federated Learning: Performance guarantees and benefits. Neurocomputing 556: 126647 (2023) - [j86]Sunwoo Lee, Chaoyang He, Salman Avestimehr:
Achieving small-batch accuracy with large-batch scalability via Hessian-aware learning rate adjustment. Neural Networks 158: 1-14 (2023) - [j85]Ahmed Roushdy Elkordy, Jiang Zhang, Yahya H. Ezzeldin, Konstantinos Psounis, Salman Avestimehr:
How Much Privacy Does Federated Learning with Secure Aggregation Guarantee? Proc. Priv. Enhancing Technol. 2023(1): 510-526 (2023) - [j84]Gökberk Elmas, Salman Ul Hassan Dar, Yilmaz Korkmaz, Emir Ceyani, Burak Susam, Muzaffer Özbey, Salman Avestimehr, Tolga Çukur:
Federated Learning of Generative Image Priors for MRI Reconstruction. IEEE Trans. Medical Imaging 42(7): 1996-2009 (2023) - [j83]Sara Babakniya, Souvik Kundu, Saurav Prakash, Yue Niu, Salman Avestimehr:
Revisiting Sparsity Hunting in Federated Learning: Why does Sparsity Consensus Matter? Trans. Mach. Learn. Res. 2023 (2023) - [j82]Erum Mushtaq, Chaoyang He, Jie Ding, Salman Avestimehr:
Distributed Architecture Search Over Heterogeneous Distributions. Trans. Mach. Learn. Res. 2023 (2023) - [j81]Yue Niu, Zalan Fabian, Sunwoo Lee, Mahdi Soltanolkotabi, Salman Avestimehr:
mL-BFGS: A Momentum-based L-BFGS for Distributed Large-scale Neural Network Optimization. Trans. Mach. Learn. Res. 2023 (2023) - [j80]Yue Niu, Saurav Prakash, Souvik Kundu, Sunwoo Lee, Salman Avestimehr:
Overcoming Resource Constraints in Federated Learning: Large Models Can Be Trained with only Weak Clients. Trans. Mach. Learn. Res. 2023 (2023) - [c167]Yahya H. Ezzeldin, Shen Yan, Chaoyang He, Emilio Ferrara, Amir Salman Avestimehr:
FairFed: Enabling Group Fairness in Federated Learning. AAAI 2023: 7494-7502 - [c166]Sunwoo Lee, Tuo Zhang, Amir Salman Avestimehr:
Layer-Wise Adaptive Model Aggregation for Scalable Federated Learning. AAAI 2023: 8491-8499 - [c165]Jinhyun So, Ramy E. Ali, Basak Güler, Jiantao Jiao, Amir Salman Avestimehr:
Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning. AAAI 2023: 9864-9873 - [c164]Joshua C. Zhao, Ahmed Roushdy Elkordy, Atul Sharma, Yahya H. Ezzeldin, Salman Avestimehr, Saurabh Bagchi:
The Resource Problem of Using Linear Layer Leakage Attack in Federated Learning. CVPR 2023: 3974-3983 - [c163]Tuo Zhang, Lei Gao, Sunwoo Lee, Mi Zhang, Salman Avestimehr:
TimelyFL: Heterogeneity-aware Asynchronous Federated Learning with Adaptive Partial Training. CVPR Workshops 2023: 5064-5073 - [c162]Baturalp Buyukates, Chaoyang He, Shanshan Han, Zhiyong Fang, Yupeng Zhang, Jieyi Long, Ali Farahanchi, Salman Avestimehr:
Proof-of-Contribution-Based Design for Collaborative Machine Learning on Blockchain. DAPPS 2023: 13-22 - [c161]Christophe Dupuy, Jimit Majmudar, Jixuan Wang, Tanya G. Roosta, Rahul Gupta, Clement Chung, Jie Ding, Salman Avestimehr:
Quantifying Catastrophic Forgetting in Continual Federated Learning. ICASSP 2023: 1-5 - [c160]Tuo Zhang, Tiantian Feng, Samiul Alam, Sunwoo Lee, Mi Zhang, Shrikanth S. Narayanan, Salman Avestimehr:
FedAudio: A Federated Learning Benchmark for Audio Tasks. ICASSP 2023: 1-5 - [c159]Erum Mushtaq, Yavuz Faruk Bakman, Jie Ding, Salman Avestimehr:
Federated Alternate Training (Fat): Leveraging Unannotated Data Silos in Federated Segmentation for Medical Imaging. ISBI 2023: 1-5 - [c158]Tiantian Feng, Digbalay Bose, Tuo Zhang, Rajat Hebbar, Anil Ramakrishna, Rahul Gupta, Mi Zhang, Salman Avestimehr, Shrikanth Narayanan:
FedMultimodal: A Benchmark for Multimodal Federated Learning. KDD 2023: 4035-4045 - [c157]Shen Li, Pritam Damania, Luca Wehrstedt, Rohan Varma, Omkar Salpekar, Pavel Belevich, Howard Huang, Yanli Zhao, Lucas Hosseini, Wanchao Liang, Hongyi Jia, Shihao Xu, Satendra Gera, Alisson G. Azzolini, Guoqiang Jerry Chen, Zachary DeVito, Chaoyang He, Amir Ziashahabi, Alban Desmaison, Edward Z. Yang, Gregory Chanan, Brian Vaughan, Manoj Krishnan, Joseph S. Spisak, Salman Avestimehr, Soumith Chintala:
PyTorch RPC: Distributed Deep Learning Built on Tensor-Optimized Remote Procedure Calls. MLSys 2023 - [c156]Sara Babakniya, Zalan Fabian, Chaoyang He, Mahdi Soltanolkotabi, Salman Avestimehr:
A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks. NeurIPS 2023 - [i188]Ahmed Roushdy Elkordy, Yahya H. Ezzeldin, Shanshan Han, Shantanu Sharma, Chaoyang He, Sharad Mehrotra, Salman Avestimehr:
Federated Analytics: A survey. CoRR abs/2302.01326 (2023) - [i187]Baturalp Buyukates, Chaoyang He, Shanshan Han, Zhiyong Fang, Yupeng Zhang, Jieyi Long, Ali Farahanchi, Salman Avestimehr:
Proof-of-Contribution-Based Design for Collaborative Machine Learning on Blockchain. CoRR abs/2302.14031 (2023) - [i186]Zhenheng Tang, Xiaowen Chu, Ryan Yide Ran, Sunwoo Lee, Shaohuai Shi, Yonggang Zhang, Yuxin Wang, Alex Qiaozhong Liang, Salman Avestimehr, Chaoyang He:
FedML Parrot: A Scalable Federated Learning System via Heterogeneity-aware Scheduling on Sequential and Hierarchical Training. CoRR abs/2303.01778 (2023) - [i185]Weizhao Jin, Yuhang Yao, Shanshan Han, Carlee Joe-Wong, Srivatsan Ravi, Salman Avestimehr, Chaoyang He:
FedML-HE: An Efficient Homomorphic-Encryption-Based Privacy-Preserving Federated Learning System. CoRR abs/2303.10837 (2023) - [i184]Joshua C. Zhao, Atul Sharma, Ahmed Roushdy Elkordy, Yahya H. Ezzeldin, Salman Avestimehr, Saurabh Bagchi:
Secure Aggregation in Federated Learning is not Private: Leaking User Data at Large Scale through Model Modification. CoRR abs/2303.12233 (2023) - [i183]Joshua C. Zhao, Ahmed Roushdy Elkordy, Atul Sharma, Yahya H. Ezzeldin, Salman Avestimehr, Saurabh Bagchi:
The Resource Problem of Using Linear Layer Leakage Attack in Federated Learning. CoRR abs/2303.14868 (2023) - [i182]Duygu Nur Yaldiz, Tuo Zhang, Salman Avestimehr:
Secure Federated Learning against Model Poisoning Attacks via Client Filtering. CoRR abs/2304.00160 (2023) - [i181]Tuo Zhang, Lei Gao, Sunwoo Lee, Mi Zhang, Salman Avestimehr:
TimelyFL: Heterogeneity-aware Asynchronous Federated Learning with Adaptive Partial Training. CoRR abs/2304.06947 (2023) - [i180]Erum Mushtaq, Yavuz Faruk Bakman, Jie Ding, Salman Avestimehr:
Federated Alternate Training (FAT): Leveraging Unannotated Data Silos in Federated Segmentation for Medical Imaging. CoRR abs/2304.09327 (2023) - [i179]Tuo Zhang, Tiantian Feng, Samiul Alam, Mi Zhang, Shrikanth S. Narayanan, Salman Avestimehr:
GPT-FL: Generative Pre-trained Model-Assisted Federated Learning. CoRR abs/2306.02210 (2023) - [i178]Shanshan Han, Baturalp Buyukates, Zijian Hu, Han Jin, Weizhao Jin, Lichao Sun, Xiaoyang Wang, Chulin Xie, Kai Zhang, Qifan Zhang, Yuhui Zhang, Chaoyang He, Salman Avestimehr:
FedMLSecurity: A Benchmark for Attacks and Defenses in Federated Learning and LLMs. CoRR abs/2306.04959 (2023) - [i177]Tiantian Feng, Digbalay Bose, Tuo Zhang, Rajat Hebbar, Anil Ramakrishna, Rahul Gupta, Mi Zhang, Salman Avestimehr, Shrikanth Narayanan:
FedMultimodal: A Benchmark For Multimodal Federated Learning. CoRR abs/2306.09486 (2023) - [i176]Sara Babakniya, Zalan Fabian, Chaoyang He, Mahdi Soltanolkotabi, Salman Avestimehr:
Don't Memorize; Mimic The Past: Federated Class Incremental Learning Without Episodic Memory. CoRR abs/2307.00497 (2023) - [i175]Yue Niu, Zalan Fabian, Sunwoo Lee, Mahdi Soltanolkotabi, Salman Avestimehr:
mL-BFGS: A Momentum-based L-BFGS for Distributed Large-Scale Neural Network Optimization. CoRR abs/2307.13744 (2023) - [i174]Sara Babakniya, Ahmed Roushdy Elkordy, Yahya H. Ezzeldin, Qingfeng Liu, Kee-Bong Song, Mostafa El-Khamy, Salman Avestimehr:
SLoRA: Federated Parameter Efficient Fine-Tuning of Language Models. CoRR abs/2308.06522 (2023) - [i173]Yavuz Faruk Bakman, Duygu Nur Yaldiz, Yahya H. Ezzeldin, Salman Avestimehr:
Federated Orthogonal Training: Mitigating Global Catastrophic Forgetting in Continual Federated Learning. CoRR abs/2309.01289 (2023) - [i172]Samiul Alam, Tuo Zhang, Tiantian Feng, Hui Shen, Zhichao Cao, Dong Zhao, JeongGil Ko, Kiran Somasundaram, Shrikanth S. Narayanan, Salman Avestimehr, Mi Zhang:
FedAIoT: A Federated Learning Benchmark for Artificial Intelligence of Things. CoRR abs/2310.00109 (2023) - [i171]Shanshan Han, Wenxuan Wu, Baturalp Buyukates, Weizhao Jin, Yuhang Yao, Qifan Zhang, Salman Avestimehr, Chaoyang He:
Kick Bad Guys Out! Zero-Knowledge-Proof-Based Anomaly Detection in Federated Learning. CoRR abs/2310.04055 (2023) - [i170]Sara Babakniya, Zalan Fabian, Chaoyang He, Mahdi Soltanolkotabi, Salman Avestimehr:
A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks. CoRR abs/2311.07784 (2023) - [i169]Yue Niu, Ramy E. Ali, Saurav Prakash, Salman Avestimehr:
All Rivers Run to the Sea: Private Learning with Asymmetric Flows. CoRR abs/2312.05264 (2023) - 2022
- [j79]Tuo Zhang, Lei Gao, Chaoyang He, Mi Zhang, Bhaskar Krishnamachari, Amir Salman Avestimehr:
Federated Learning for the Internet of Things: Applications, Challenges, and Opportunities. IEEE Internet Things Mag. 5(1): 24-29 (2022) - [j78]Sennur Ulukus, Salman Avestimehr, Michael Gastpar, Syed Ali Jafar, Ravi Tandon, Chao Tian:
Privacy in Retrieval, Computing, and Learning. IEEE J. Sel. Areas Commun. 40(3): 725-728 (2022) - [j77]Sennur Ulukus, Salman Avestimehr, Michael Gastpar, Syed Ali Jafar, Ravi Tandon, Chao Tian:
Private Retrieval, Computing, and Learning: Recent Progress and Future Challenges. IEEE J. Sel. Areas Commun. 40(3): 729-748 (2022) - [j76]Ahmed Roushdy Elkordy, Saurav Prakash, Salman Avestimehr:
Basil: A Fast and Byzantine-Resilient Approach for Decentralized Training. IEEE J. Sel. Areas Commun. 40(9): 2694-2716 (2022) - [j75]Mohammad Ali Maddah-Ali, Salman Avestimehr, Ravi Tandon, Changho Suh, Ayfer Özgür, Chao Tian, Tara Javidi, Giuseppe Caire:
Guest Editorial. IEEE J. Sel. Areas Inf. Theory 3(2): 161 (2022) - [j74]Yue Niu, Ramy E. Ali, Salman Avestimehr:
3LegRace: Privacy-Preserving DNN Training over TEEs and GPUs. Proc. Priv. Enhancing Technol. 2022(4): 183-203 (2022) - [j73]Ahmed Roushdy Elkordy, Amir Salman Avestimehr:
HeteroSAg: Secure Aggregation With Heterogeneous Quantization in Federated Learning. IEEE Trans. Commun. 70(4): 2372-2386 (2022) - [j72]Saeid Sahraei, Amir Salman Avestimehr, Ramy E. Ali:
Info-Commit: Information-Theoretic Polynomial Commitment. IEEE Trans. Inf. Forensics Secur. 17: 1698-1708 (2022) - [j71]Mahdi Soleymani, Hessam Mahdavifar, Amir Salman Avestimehr:
Analog Secret Sharing With Applications to Private Distributed Learning. IEEE Trans. Inf. Forensics Secur. 17: 1893-1904 (2022) - [j70]Amirhossein Reisizadeh, Saurav Prakash, Ramtin Pedarsani, Amir Salman Avestimehr:
CodedReduce: A Fast and Robust Framework for Gradient Aggregation in Distributed Learning. IEEE/ACM Trans. Netw. 30(1): 148-161 (2022) - [c155]Chaoyang He, Emir Ceyani, Keshav Balasubramanian, Murali Annavaram, Salman Avestimehr:
SpreadGNN: Decentralized Multi-Task Federated Learning for Graph Neural Networks on Molecular Data. AAAI 2022: 6865-6873 - [c154]Mahdi Soleymani, Ramy E. Ali, Hessam Mahdavifar, Amir Salman Avestimehr:
ApproxIFER: A Model-Agnostic Approach to Resilient and Robust Prediction Serving Systems. AAAI 2022: 8342-8350 - [c153]August Deer, Ramy E. Ali, Amir Salman Avestimehr:
On Multi-Round Privacy in Federated Learning. IEEECONF 2022: 764-769 - [c152]Yaying Shi, Hongjian Gao, Salman Avestimehr, Yonghong Yan:
Experimenting FedML and NVFLARE for Federated Tumor Segmentation Challenge. BrainLes@MICCAI (2) 2022: 228-240 - [c151]Ahmed Roushdy Elkordy, Yahya H. Ezzeldin, Salman Avestimehr:
Federated K-Private Set Intersection. CIKM 2022: 436-445 - [c150]Carl Yang, Xiaoxiao Li, Nathalie Baracaldo, Neil Shah, Chaoyang He, Lingjuan Lyu, Lichao Sun, Salman Avestimehr:
The 1st International Workshop on Federated Learning with Graph Data (FedGraph). CIKM 2022: 5179-5180 - [c149]Xiaoyi Mai, Salman Avestimehr, Antonio Ortega, Mahdi Soltanolkotabi:
On The Effectiveness of Active Learning by Uncertainty Sampling in Classification of High-Dimensional Gaussian Mixture Data. ICASSP 2022: 4238-4242 - [c148]Jie Ding, Eric W. Tramel, Anit Kumar Sahu, Shuang Wu, Salman Avestimehr, Tao Zhang:
Federated Learning Challenges and Opportunities: An Outlook. ICASSP 2022: 8752-8756 - [c147]Christophe Dupuy, Tanya G. Roosta, Leo Long, Clement Chung, Rahul Gupta, Salman Avestimehr:
Learnings from Federated Learning in The Real World. ICASSP 2022: 8767-8771 - [c146]Erum Mushtaq, Jie Ding, Salman Avestimehr:
What If Kidney Tumor Segmentation Challenge (KiTS19) Never Happened. ICMLA 2022: 1740-1747 - [c145]Tingting Tang, Ramy E. Ali, Hanieh Hashemi, Tynan Gangwani, Salman Avestimehr, Murali Annavaram:
Adaptive Verifiable Coded Computing: Towards Fast, Secure and Private Distributed Machine Learning. IPDPS 2022: 628-638 - [c144]Seyed Mohammadreza Mousavi Kalan, Mahdi Soltanolkotabi, Amir Salman Avestimehr:
Statistical Minimax Lower Bounds for Transfer Learning in Linear Binary Classification. ISIT 2022: 282-287 - [c143]Jinhyun So, Corey J. Nolet, Chien-Sheng Yang, Songze Li, Qian Yu, Ramy E. Ali, Basak Guler, Salman Avestimehr:
LightSecAgg: a Lightweight and Versatile Design for Secure Aggregation in Federated Learning. MLSys 2022 - [c142]Bill Yuchen Lin, Chaoyang He, Zihang Ze, Hulin Wang, Yufen Hua, Christophe Dupuy, Rahul Gupta, Mahdi Soltanolkotabi, Xiang Ren, Salman Avestimehr:
FedNLP: Benchmarking Federated Learning Methods for Natural Language Processing Tasks. NAACL-HLT (Findings) 2022: 157-175 - [c141]Rahul Sharma, Anil Ramakrishna, Ansel MacLaughlin, Anna Rumshisky, Jimit Majmudar, Clement Chung, Salman Avestimehr, Rahul Gupta:
Federated Learning with Noisy User Feedback. NAACL-HLT 2022: 2726-2739 - [c140]Huili Chen, Jie Ding, Eric W. Tramel, Shuang Wu, Anit Kumar Sahu, Salman Avestimehr, Tao Zhang:
Self-Aware Personalized Federated Learning. NeurIPS 2022 - [c139]Jean Ogier du Terrail, Samy-Safwan Ayed, Edwige Cyffers, Felix Grimberg, Chaoyang He, Regis Loeb, Paul Mangold, Tanguy Marchand, Othmane Marfoq, Erum Mushtaq, Boris Muzellec, Constantin Philippenko, Santiago Silva, Maria Telenczuk, Shadi Albarqouni, Salman Avestimehr, Aurélien Bellet, Aymeric Dieuleveut, Martin Jaggi, Sai Praneeth Karimireddy, Marco Lorenzi, Giovanni Neglia, Marc Tommasi, Mathieu Andreux:
FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings. NeurIPS 2022 - [i168]Sunwoo Lee, Anit Kumar Sahu, Chaoyang He, Salman Avestimehr:
Partial Model Averaging in Federated Learning: Performance Guarantees and Benefits. CoRR abs/2201.03789 (2022) - [i167]Jie Ding, Eric W. Tramel, Anit Kumar Sahu, Shuang Wu, Salman Avestimehr, Tao Zhang:
Federated Learning Challenges and Opportunities: An Outlook. CoRR abs/2202.00807 (2022) - [i166]Jinhyun So, Kevin Hsieh, Behnaz Arzani, Shadi A. Noghabi, Salman Avestimehr, Ranveer Chandra:
FedSpace: An Efficient Federated Learning Framework at Satellites and Ground Stations. CoRR abs/2202.01267 (2022) - [i165]Christophe Dupuy, Tanya G. Roosta, Leo Long, Clement Chung, Rahul Gupta, Salman Avestimehr:
Learnings from Federated Learning in the Real world. CoRR abs/2202.03925 (2022) - [i164]Gökberk Elmas, Salman Ul Hassan Dar, Yilmaz Korkmaz, Emir Ceyani, Burak Susam, Muzaffer Özbey, Salman Avestimehr, Tolga Çukur:
Federated Learning of Generative Image Priors for MRI Reconstruction. CoRR abs/2202.04175 (2022) - [i163]Huili Chen, Jie Ding, Eric W. Tramel, Shuang Wu, Anit Kumar Sahu, Salman Avestimehr, Tao Zhang:
Self-Aware Personalized Federated Learning. CoRR abs/2204.08069 (2022) - [i162]Rahul Sharma, Anil Ramakrishna, Ansel MacLaughlin, Anna Rumshisky, Jimit Majmudar, Clement Chung, Salman Avestimehr, Rahul Gupta:
Federated Learning with Noisy User Feedback. CoRR abs/2205.03092 (2022) - [i161]Romain Cosentino, Anirvan M. Sengupta, Salman Avestimehr, Mahdi Soltanolkotabi, Antonio Ortega, Theodore L. Willke, Mariano Tepper:
Toward a Geometrical Understanding of Self-supervised Contrastive Learning. CoRR abs/2205.06926 (2022) - [i160]Songze Li, Sizai Hou, Baturalp Buyukates, Salman Avestimehr:
Secure Federated Clustering. CoRR abs/2205.15564 (2022) - [i159]Onat Dalmaz, Muhammad Usama Mirza, Gökberk Elmas, Muzaffer Özbey, Salman Ul Hassan Dar, Emir Ceyani, Salman Avestimehr, Tolga Çukur:
One Model to Unite Them All: Personalized Federated Learning of Multi-Contrast MRI Synthesis. CoRR abs/2207.06509 (2022) - [i158]Ahmed Roushdy Elkordy, Jiang Zhang, Yahya H. Ezzeldin, Konstantinos Psounis, Salman Avestimehr:
How Much Privacy Does Federated Learning with Secure Aggregation Guarantee? CoRR abs/2208.02304 (2022) - [i157]Sara Babakniya, Souvik Kundu, Saurav Prakash, Yue Niu, Salman Avestimehr:
Federated Sparse Training: Lottery Aware Model Compression for Resource Constrained Edge. CoRR abs/2208.13092 (2022) - [i156]Yue Niu, Saurav Prakash, Souvik Kundu, Sunwoo Lee, Salman Avestimehr:
Federated Learning of Large Models at the Edge via Principal Sub-Model Training. CoRR abs/2208.13141 (2022) - [i155]Romain Cosentino, Sarath Shekkizhar, Mahdi Soltanolkotabi, Salman Avestimehr, Antonio Ortega:
The Geometry of Self-supervised Learning Models and its Impact on Transfer Learning. CoRR abs/2209.08622 (2022) - [i154]Jean Ogier du Terrail, Samy-Safwan Ayed, Edwige Cyffers, Felix Grimberg, Chaoyang He, Regis Loeb, Paul Mangold, Tanguy Marchand, Othmane Marfoq, Erum Mushtaq, Boris Muzellec, Constantin Philippenko, Santiago Silva, Maria Telenczuk, Shadi Albarqouni, Salman Avestimehr, Aurélien Bellet, Aymeric Dieuleveut, Martin Jaggi, Sai Praneeth Karimireddy, Marco Lorenzi, Giovanni Neglia, Marc Tommasi, Mathieu Andreux:
FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings. CoRR abs/2210.04620 (2022) - [i153]Tuo Zhang, Tiantian Feng, Samiul Alam, Sunwoo Lee, Mi Zhang, Shrikanth S. Narayanan, Salman Avestimehr:
FedAudio: A Federated Learning Benchmark for Audio Tasks. CoRR abs/2210.15707 (2022) - [i152]