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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
- 2023
[j82]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)- [j81]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) - [j80]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) - [c155]Yahya H. Ezzeldin, Shen Yan, Chaoyang He, Emilio Ferrara, Amir Salman Avestimehr:
FairFed: Enabling Group Fairness in Federated Learning. AAAI 2023: 7494-7502 - [c154]Sunwoo Lee, Tuo Zhang, Amir Salman Avestimehr:
Layer-Wise Adaptive Model Aggregation for Scalable Federated Learning. AAAI 2023: 8491-8499 - [c153]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 - [c152]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 - [c151]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 - [c150]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 - [c149]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 - [c148]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 - [i184]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) - [i183]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) - [i182]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) - [i181]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) - [i180]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) - [i179]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) - [i178]Duygu Nur Yaldiz, Tuo Zhang, Salman Avestimehr:
Secure Federated Learning against Model Poisoning Attacks via Client Filtering. CoRR abs/2304.00160 (2023) - [i177]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) - [i176]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) - [i175]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) - [i174]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) - [i173]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) - [i172]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) - [i171]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) - [i170]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) - [i169]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) - 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) - [c147]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 - [c146]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 - [c145]August Deer, Ramy E. Ali, Amir Salman Avestimehr:
On Multi-Round Privacy in Federated Learning. IEEECONF 2022: 764-769 - [c144]Ahmed Roushdy Elkordy, Yahya H. Ezzeldin, Salman Avestimehr:
Federated K-Private Set Intersection. CIKM 2022: 436-445 - [c143]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 - [c142]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 - [c141]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 - [c140]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 - [c139]Erum Mushtaq, Jie Ding, Salman Avestimehr:
What If Kidney Tumor Segmentation Challenge (KiTS19) Never Happened. ICMLA 2022: 1740-1747 - [c138]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 - [c137]Seyed Mohammadreza Mousavi Kalan, Mahdi Soltanolkotabi, Amir Salman Avestimehr:
Statistical Minimax Lower Bounds for Transfer Learning in Linear Binary Classification. ISIT 2022: 282-287 - [c136]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 - [c135]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 - [c134]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 - [c133]Huili Chen, Jie Ding, Eric W. Tramel, Shuang Wu, Anit Kumar Sahu, Salman Avestimehr, Tao Zhang:
Self-Aware Personalized Federated Learning. NeurIPS 2022 - [c132]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 S. Silva R., 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]Chaoyang He, Shuai Zheng, Aston Zhang, George Karypis, Trishul Chilimbi, Mahdi Soltanolkotabi, Salman Avestimehr:
SMILE: Scaling Mixture-of-Experts with Efficient Bi-level Routing. CoRR abs/2212.05191 (2022) - [i151]Songze Li, Sizai Hou, Baturalp Buyukates, Salman Avestimehr:
Secure Federated Clustering. IACR Cryptol. ePrint Arch. 2022: 682 (2022) - 2021
- [j69]Saurav Prakash, Sagar Dhakal, Mustafa Riza Akdeniz, Yair Yona, Shilpa Talwar, Salman Avestimehr, Nageen Himayat:
Coded Computing for Low-Latency Federated Learning Over Wireless Edge Networks. IEEE J. Sel. Areas Commun. 39(1): 233-250 (2021) - [j68]Jinhyun So, Basak Güler, Amir Salman Avestimehr:
Byzantine-Resilient Secure Federated Learning. IEEE J. Sel. Areas Commun. 39(7): 2168-2181 (2021) - [j67]Mahdi Soleymani, Hessam Mahdavifar, Amir Salman Avestimehr:
Analog Lagrange Coded Computing. IEEE J. Sel. Areas Inf. Theory 2(1): 283-295 (2021) - [j66]Saeid Sahraei, Mohammad Ali Maddah-Ali, Amir Salman Avestimehr:
Interactive Verifiable Polynomial Evaluation. IEEE J. Sel. Areas Inf. Theory 2(1): 317-325 (2021) - [j65]Chien-Sheng Yang, Amir Salman Avestimehr:
Coded Computing for Secure Boolean Computations. IEEE J. Sel. Areas Inf. Theory 2(1): 326-337 (2021) - [j64]Jinhyun So, Basak Güler, Amir Salman Avestimehr:
CodedPrivateML: A Fast and Privacy-Preserving Framework for Distributed Machine Learning. IEEE J. Sel. Areas Inf. Theory 2(1): 441-451 (2021) - [j63]Jinhyun So, Basak Güler, Amir Salman Avestimehr:
Turbo-Aggregate: Breaking the Quadratic Aggregation Barrier in Secure Federated Learning. IEEE J. Sel. Areas Inf. Theory 2(1): 479-489 (2021) - [j62]Pulkit Grover, Viveck R. Cadambe, Sennur Ulukus, Stark C. Draper, Salman Avestimehr, Osvaldo Simeone:
Guest Editorial for Special Issue on Coded Computing. IEEE J. Sel. Areas Inf. Theory 2(3): 813 (2021) - [j61]Mahdi Soleymani, Ramy E. Ali, Hessam Mahdavifar, Amir Salman Avestimehr:
List-Decodable Coded Computing: Breaking the Adversarial Toleration Barrier. IEEE J. Sel. Areas Inf. Theory 2(3): 867-878 (2021) - [j60]Qian Yu, Amir Salman Avestimehr:
Coded Computing for Resilient, Secure, and Privacy-Preserving Distributed Matrix Multiplication. IEEE Trans. Commun. 69(1): 59-72 (2021) - [j59]Ahmed Roushdy Elkordy, Songze Li, Mohammad Ali Maddah-Ali, Amir Salman Avestimehr:
Compressed Coded Distributed Computing. IEEE Trans. Commun. 69(5): 2773-2783 (2021) - [j58]Songze Li, Mingchao Yu, Chien-Sheng Yang, Amir Salman Avestimehr, Sreeram Kannan, Pramod Viswanath:
PolyShard: Coded Sharding Achieves Linearly Scaling Efficiency and Security Simultaneously. IEEE Trans. Inf. Forensics Secur. 16: 249-261 (2021) - [j57]Chien-Sheng Yang, Ramtin Pedarsani, Amir Salman Avestimehr:
Edge Computing in the Dark: Leveraging Contextual-Combinatorial Bandit and Coded Computing. IEEE/ACM Trans. Netw. 29(3): 1022-1031 (2021) - [c131]Yaying Shi, Christian Micklisch, Erum Mushtaq, Salman Avestimehr, Yonghong Yan, Xiaodong Zhang:
An Ensemble Approach to Automatic Brain Tumor Segmentation. BrainLes@MICCAI (2) 2021: 138-148 - [c130]Chaoyang He, Shen Li, Mahdi Soltanolkotabi, Salman Avestimehr:
PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models. ICML 2021: 4150-4159 - [c129]Mahdi Soleymani, Ramy E. Ali, Hessam Mahdavifar, Amir Salman Avestimehr:
List-Decodable Coded Computing: Breaking the Adversarial Toleration Barrier. ISIT 2021: 1206-1211 - [c128]Mahdi Soleymani, Hessam Mahdavifar, Amir Salman Avestimehr:
Analog Privacy-Preserving Coded Computing. ISIT 2021: 1865-1870 - [c127]Alexander Poylisher, Andrzej Cichocki, Katherine Guo, James Hunziker, Latha A. Kant, Bhaskar Krishnamachari, Salman Avestimehr, Murali Annavaram:
Tactical Jupiter: Dynamic Scheduling of Dispersed Computations in Tactical MANETs. MILCOM 2021: 102-107 - [c126]Tuo Zhang, Chaoyang He, Tianhao Ma, Lei Gao, Mark Ma, Salman Avestimehr:
Federated Learning for Internet of Things. SenSys 2021: 413-419 - [c125]Pradipta Ghosh, Quynh Nguyen, Pranav K. Sakulkar, Jason A. Tran, Aleksandra Knezevic, Jiatong Wang, Zhifeng Lin, Bhaskar Krishnamachari, Murali Annavaram, Salman Avestimehr:
Jupiter: a networked computing architecture. UCC Companion 2021: 28:1-28:8 - [i150]Mahdi Soleymani, Ramy E. Ali, Hessam Mahdavifar, Amir Salman Avestimehr:
List-Decodable Coded Computing: Breaking the Adversarial Toleration Barrier. CoRR abs/2101.11653 (2021) - [i149]Chaoyang He, Shen Li, Mahdi Soltanolkotabi, Salman Avestimehr:
PipeTransformer: Automated Elastic Pipelining for Distributed Training of Transformers. CoRR abs/2102.03161 (2021) - [i148]Chaoyang He, Keshav Balasubramanian, Emir Ceyani, Yu Rong, Peilin Zhao, Junzhou Huang, Murali Annavaram, Salman Avestimehr:
FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks. CoRR abs/2104.07145 (2021) - [i147]Bill Yuchen Lin, Chaoyang He, Zihang Zeng, Hulin Wang, Yufen Huang, Mahdi Soltanolkotabi, Xiang Ren, Salman Avestimehr:
FedNLP: A Research Platform for Federated Learning in Natural Language Processing. CoRR abs/2104.08815 (2021) - [i146]Chaoyang He, Emir Ceyani, Keshav Balasubramanian, Murali Annavaram, Salman Avestimehr:
SpreadGNN: Serverless Multi-task Federated Learning for Graph Neural Networks. CoRR abs/2106.02743 (2021) - [i145]Jinhyun So, Ramy E. Ali, Basak Guler, Jiantao Jiao, Salman Avestimehr:
Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning. CoRR abs/2106.03328 (2021) - [i144]Tuo Zhang, Chaoyang He, Tianhao Ma, Mark Ma, Salman Avestimehr:
Federated Learning for Internet of Things: A Federated Learning Framework for On-device Anomaly Data Detection. CoRR abs/2106.07976 (2021) - [i143]Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Agüera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas N. Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horváth, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecný, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtárik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake E. Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu:
A Field Guide to Federated Optimization. CoRR abs/2107.06917 (2021) - [i142]Tingting Tang, Ramy E. Ali, Hanieh Hashemi, Tynan Gangwani, Salman Avestimehr, Murali Annavaram:
Verifiable Coded Computing: Towards Fast, Secure and Private Distributed Machine Learning. CoRR abs/2107.12958 (2021) - [i141]Sennur Ulukus, Salman Avestimehr, Michael Gastpar, Syed Ali Jafar, Ravi Tandon, Chao Tian:
Private Retrieval, Computing and Learning: Recent Progress and Future Challenges. CoRR abs/2108.00026 (2021) - [i140]Ahmed Roushdy Elkordy, Saurav Prakash, Amir Salman Avestimehr:
Basil: A Fast and Byzantine-Resilient Approach for Decentralized Training. CoRR abs/2109.07706 (2021) - [i139]Mahdi Soleymani, Ramy E. Ali, Hessam Mahdavifar, Amir Salman Avestimehr:
ApproxIFER: A Model-Agnostic Approach to Resilient and Robust Prediction Serving Systems. CoRR abs/2109.09868 (2021) - [i138]Chien-Sheng Yang, Jinhyun So, Chaoyang He, Songze Li, Qian Yu, Salman Avestimehr:
LightSecAgg: Rethinking Secure Aggregation in Federated Learning. CoRR abs/2109.14236 (2021) - [i137]Yahya H. Ezzeldin, Shen Yan, Chaoyang He, Emilio Ferrara, Salman Avestimehr:
FairFed: Enabling Group Fairness in Federated Learning. CoRR abs/2110.00857 (2021) - [i136]Yue Niu, Ramy E. Ali, Salman Avestimehr:
AsymML: An Asymmetric Decomposition Framework for Privacy-Preserving DNN Training and Inference. CoRR abs/2110.01229 (2021) - [i135]Jinhyun So, Ramy E. Ali, Basak Güler, Amir Salman Avestimehr:
Secure Aggregation for Buffered Asynchronous Federated Learning. CoRR abs/2110.02177 (2021) - [i134]Chaoyang He, Zhengyu Yang, Erum Mushtaq, Sunwoo Lee, Mahdi Soltanolkotabi, Salman Avestimehr:
SSFL: Tackling Label Deficiency in Federated Learning via Personalized Self-Supervision. CoRR abs/2110.02470 (2021) - [i133]Sunwoo Lee, Tuo Zhang, Chaoyang He, Salman Avestimehr:
Layer-wise Adaptive Model Aggregation for Scalable Federated Learning. CoRR abs/2110.10302 (2021) - [i132]Tuo Zhang, Lei Gao, Chaoyang He, Mi Zhang, Bhaskar Krishnamachari, Salman Avestimehr:
Federated Learning for Internet of Things: Applications, Challenges, and Opportunities. CoRR abs/2111.07494 (2021) - [i131]