Salman Avestimehr

ORCID

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 163

Top Venues

CoRR

NeurIPS

ICASSP

Proc. Priv. Enhancing Technol.

Publications

Hamza Saleem, Amir Ziashahabi, Muhammad Naveed, Salman Avestimehr
Hawk: Accurate and Fast Privacy-Preserving Machine Learning Using Secure Lookup Table Computation. CoRR (2024)
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)
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 (2024)
Tingting Tang, Yue Niu, Salman Avestimehr, Murali Annavaram
Edge Private Graph Neural Networks with Singular Value Perturbation. Proc. Priv. Enhancing Technol. 2024 (3) (2024)
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)
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 (2024)
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 (2024)
Sunwoo Lee, Tuo Zhang, Saurav Prakash, Yue Niu, Salman Avestimehr
Embracing Federated Learning: Enabling Weak Client Participation via Partial Model Training. CoRR (2024)
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 (2024)
Lei Gao, Yue Niu, Tingting Tang, Salman Avestimehr, Murali Annavaram
Ethos: Rectifying Language Models in Orthogonal Parameter Space. CoRR (2024)
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) (2024)
Tingting Tang, Yue Niu, Salman Avestimehr, Murali Annavaram
Edge Private Graph Neural Networks with Singular Value Perturbation. CoRR (2024)
Tuo Zhang, Jinyue Yuan, Salman Avestimehr
Revisiting OPRO: The Limitations of Small-Scale LLMs as Optimizers. CoRR (2024)
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 (2024)
Yavuz Faruk Bakman, Duygu Nur Yaldiz, Yahya H. Ezzeldin, Salman Avestimehr
Federated Orthogonal Training: Mitigating Global Catastrophic Forgetting in Continual Federated Learning. ICLR (2024)
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)
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 (2024)
Tuo Zhang, Jinyue Yuan, Salman Avestimehr
Revisiting OPRO: The Limitations of Small-Scale LLMs as Optimizers. ACL (Findings) (2024)
Mengwei Yang, Ismat Jarin, Baturalp Buyukates, Salman Avestimehr, Athina Markopoulou
Maverick-Aware Shapley Valuation for Client Selection in Federated Learning. CoRR (2024)
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 (2024)
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 (2024)
Yue Niu, Saurav Prakash, Salman Avestimehr
ATP: Enabling Fast LLM Serving via Attention on Top Principal Keys. CoRR (2024)
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 (2024)
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)
Tuo Zhang, Lei Gao, Sunwoo Lee, Mi Zhang, Salman Avestimehr
TimelyFL: Heterogeneity-aware Asynchronous Federated Learning with Adaptive Partial Training. CVPR Workshops (2023)
Sunwoo Lee, Anit Kumar Sahu, Chaoyang He, Salman Avestimehr
Partial model averaging in Federated Learning: Performance guarantees and benefits. Neurocomputing 556 (2023)
Yue Niu, Ramy E. Ali, Saurav Prakash, Salman Avestimehr
All Rivers Run to the Sea: Private Learning with Asymmetric Flows. CoRR (2023)
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)
Tuo Zhang, Lei Gao, Sunwoo Lee, Mi Zhang, Salman Avestimehr
TimelyFL: Heterogeneity-aware Asynchronous Federated Learning with Adaptive Partial Training. CoRR (2023)
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) (2023)
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) (2023)
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 (2023)
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 (2023)
Duygu Nur Yaldiz, Tuo Zhang, Salman Avestimehr
Secure Federated Learning against Model Poisoning Attacks via Client Filtering. CoRR (2023)
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 (2023)
Erum Mushtaq, Chaoyang He, Jie Ding, Salman Avestimehr
Distributed Architecture Search Over Heterogeneous Distributions. Trans. Mach. Learn. Res. 2023 (2023)
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)
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)
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)
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)
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 (2023)
Erum Mushtaq, Yavuz Faruk Bakman, Jie Ding, Salman Avestimehr
Federated Alternate Training (FAT): Leveraging Unannotated Data Silos in Federated Segmentation for Medical Imaging. CoRR (2023)
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 (2023)
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 (2023)
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 (2023)
Ahmed Roushdy Elkordy, Yahya H. Ezzeldin, Shanshan Han, Shantanu Sharma, Chaoyang He, Sharad Mehrotra, Salman Avestimehr
Federated Analytics: A survey. CoRR (2023)
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 (2023)
Sunwoo Lee, Chaoyang He, Salman Avestimehr
Achieving small-batch accuracy with large-batch scalability via Hessian-aware learning rate adjustment. Neural Networks 158 (2023)
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)
Tuo Zhang, Tiantian Feng, Samiul Alam, Mi Zhang, Shrikanth S. Narayanan, Salman Avestimehr
GPT-FL: Generative Pre-trained Model-Assisted Federated Learning. CoRR (2023)
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)
Sara Babakniya, Zalan Fabian, Chaoyang He, Mahdi Soltanolkotabi, Salman Avestimehr
Don't Memorize; Mimic The Past: Federated Class Incremental Learning Without Episodic Memory. CoRR (2023)
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 (2023)
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 (2023)
Yavuz Faruk Bakman, Duygu Nur Yaldiz, Yahya H. Ezzeldin, Salman Avestimehr
Federated Orthogonal Training: Mitigating Global Catastrophic Forgetting in Continual Federated Learning. CoRR (2023)
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)
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)
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 (2023)
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 (2023)
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)
Ahmed Roushdy Elkordy, Yahya H. Ezzeldin, Salman Avestimehr
Federated K-Private Set Intersection. CIKM (2022)
Rahul Sharma, Anil Ramakrishna, Ansel MacLaughlin, Anna Rumshisky, Jimit Majmudar, Clement Chung, Salman Avestimehr, Rahul Gupta
Federated Learning with Noisy User Feedback. CoRR (2022)
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)
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) (2022)
Sunwoo Lee, Anit Kumar Sahu, Chaoyang He, Salman Avestimehr
Partial Model Averaging in Federated Learning: Performance Guarantees and Benefits. CoRR (2022)
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 (2022)
Christophe Dupuy, Tanya G. Roosta, Leo Long, Clement Chung, Rahul Gupta, Salman Avestimehr
Learnings from Federated Learning in The Real World. ICASSP (2022)
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)
Onat Dalmaz, 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 (2022)
Ahmed Roushdy Elkordy, Saurav Prakash, Salman Avestimehr
Basil: A Fast and Byzantine-Resilient Approach for Decentralized Training. IEEE J. Sel. Areas Commun. 40 (9) (2022)
Songze Li, Sizai Hou, Baturalp Buyukates, Salman Avestimehr
Secure Federated Clustering. CoRR (2022)
Gokberk 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 (2022)
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)
Jie Ding, Eric Tramel, Anit Kumar Sahu, Shuang Wu, Salman Avestimehr, Tao Zhang
Federated Learning Challenges and Opportunities: An Outlook. ICASSP (2022)
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) (2022)
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)
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) (2022)
Jie Ding, Eric Tramel, Anit Kumar Sahu, Shuang Wu, Salman Avestimehr, Tao Zhang
Federated Learning Challenges and Opportunities: An Outlook. CoRR (2022)
Yaying Shi, Hongjian Gao, Salman Avestimehr, Yonghong Yan
Experimenting FedML and NVFLARE for Federated Tumor Segmentation Challenge. BrainLes@MICCAI (2) (2022)
Songze Li, Sizai Hou, Baturalp Buyukates, Salman Avestimehr
Secure Federated Clustering. IACR Cryptol. ePrint Arch. 2022 (2022)
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)
Huili Chen, Jie Ding, Eric Tramel, Shuang Wu, Anit Kumar Sahu, Salman Avestimehr, Tao Zhang
Self-Aware Personalized Federated Learning. CoRR (2022)
Sara Babakniya, Souvik Kundu, Saurav Prakash, Yue Niu, Salman Avestimehr
Federated Sparse Training: Lottery Aware Model Compression for Resource Constrained Edge. CoRR (2022)
Tuo Zhang, Tiantian Feng, Samiul Alam, Sunwoo Lee, Mi Zhang, Shrikanth S. Narayanan, Salman Avestimehr
FedAudio: A Federated Learning Benchmark for Audio Tasks. CoRR (2022)
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 (2022)
Yue Niu, Saurav Prakash, Souvik Kundu, Sunwoo Lee, Salman Avestimehr
Federated Learning of Large Models at the Edge via Principal Sub-Model Training. CoRR (2022)
Christophe Dupuy, Tanya G. Roosta, Leo Long, Clement Chung, Rahul Gupta, Salman Avestimehr
Learnings from Federated Learning in the Real world. CoRR (2022)
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 (2022)
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)
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)
Erum Mushtaq, Jie Ding, Salman Avestimehr
What If Kidney Tumor Segmentation Challenge (KiTS19) Never Happened. ICMLA (2022)
Jinhyun So, Kevin Hsieh, Behnaz Arzani, Shadi Noghabi, Salman Avestimehr, Ranveer Chandra
FedSpace: An Efficient Federated Learning Framework at Satellites and Ground Stations. CoRR (2022)
Huili Chen, Jie Ding, Eric W. Tramel, Shuang Wu, Anit Kumar Sahu, Salman Avestimehr, Tao Zhang
Self-Aware Personalized Federated Learning. NeurIPS (2022)
Yue Niu, Ramy E. Ali, Salman Avestimehr
3LegRace: Privacy-Preserving DNN Training over TEEs and GPUs. Proc. Priv. Enhancing Technol. 2022 (4) (2022)
Romain Cosentino, Sarath Shekkizhar, Mahdi Soltanolkotabi, Salman Avestimehr, Antonio Ortega
The Geometry of Self-supervised Learning Models and its Impact on Transfer Learning. CoRR (2022)
Ahmed Roushdy Elkordy, Jiang Zhang, Yahya H. Ezzeldin, Konstantinos Psounis, Salman Avestimehr
How Much Privacy Does Federated Learning with Secure Aggregation Guarantee? CoRR (2022)
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)
Chaoyang He, Alay Dilipbhai Shah, Zhenheng Tang, Di Fan, Adarshan Naiynar Sivashunmugam, Keerti Bhogaraju, Mita Shimpi, Li Shen, Xiaowen Chu, Mahdi Soltanolkotabi, Salman Avestimehr
FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks. CoRR (2021)
Jinhyun So, Ramy E. Ali, Basak Guler, Jiantao Jiao, Salman Avestimehr
Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning. IACR Cryptol. ePrint Arch. 2021 (2021)
Chaoyang He, Emir Ceyani, Keshav Balasubramanian, Murali Annavaram, Salman Avestimehr
SpreadGNN: Serverless Multi-task Federated Learning for Graph Neural Networks. CoRR (2021)

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Publication Activity (10 Years)

Top Topics

Top Venues

Salman Avestimehr