Avestimehr, Salman

33 publications

NeurIPS 2025 FALCON: An ML Framework for Fully Automated Layout-Constrained Analog Circuit Design Asal Mehradfar, Xuzhe Zhao, Yilun Huang, Emir Ceyani, Yankai Yang, Shihao Han, Hamidreza Aghasi, Salman Avestimehr

CVPRW 2025 GPT-FL: Generative Pre-Trained Model-Assisted Federated Learning Tuo Zhang, Tiantian Feng, Samiul Alam, Dimitrios Dimitriadis, Sunwoo Lee, Mi Zhang, Shrikanth S. Narayanan, Salman Avestimehr

CVPRW 2025 HARMONY: Hidden Activation Representations and Model Output-Aware Uncertainty Estimation for Vision-Language Models Erum Mushtaq, Zalan Fabian, Yavuz Faruk Bakman, Anil Ramakrishna, Mahdi Soltanolkotabi, Salman Avestimehr

CVPR 2024 All Rivers Run to the Sea: Private Learning with Asymmetric Flows Yue Niu, Ramy E. Ali, Saurav Prakash, Salman Avestimehr

ECCV 2024 CroMo-Mixup: Augmenting Cross-Model Representations for Continual Self-Supervised Learning Erum Mushtaq, Duygu Nur Yaldiz, Yavuz Faruk Bakman, Jie Ding, Chenyang Tao, Dimitrios Dimitriadis, Salman Avestimehr

DMLR 2024 FedAIoT: A Federated Learning Benchmark for Artificial Intelligence of Things Samiul Alam, Tuo Zhang, Tiantian Feng, Hui Shen, Zhichao Cao, Dong Zhao, Jeonggil Ko, Kiran Somasundaram, Shrikanth Narayanan, Salman Avestimehr, Mi Zhang

ICLR 2024 Federated Orthogonal Training: Mitigating Global Catastrophic Forgetting in Continual Federated Learning Yavuz Faruk Bakman, Duygu Nur Yaldiz, Yahya H. Ezzeldin, Salman Avestimehr

ICLRW 2024 MARS: Meaning-Aware Response Scoring for Uncertainty Estimation in Generative LLMs Yavuz Faruk Bakman, Duygu Nur Yaldiz, Baturalp Buyukates, Chenyang Tao, Dimitrios Dimitriadis, Salman Avestimehr

NeurIPS 2023 A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks Sara Babakniya, Zalan Fabian, Chaoyang He, Mahdi Soltanolkotabi, Salman Avestimehr

TMLR 2023 Distributed Architecture Search over Heterogeneous Distributions Erum Mushtaq, Chaoyang He, Jie Ding, Salman Avestimehr

ICMLW 2023 Don’t Memorize; Mimic the past: Federated Class Incremental Learning Without Episodic Memory Sara Babakniya, Zalan Fabian, Chaoyang He, Mahdi Soltanolkotabi, Salman Avestimehr

NeurIPSW 2023 FedML-HE: An Efficient Homomorphic-Encryption-Based Privacy-Preserving Federated Learning System Weizhao Jin, Yuhang Yao, Shanshan Han, Carlee Joe-Wong, Srivatsan Ravi, Salman Avestimehr, Chaoyang He

TMLR 2023 Overcoming Resource Constraints in Federated Learning: Large Models Can Be Trained with Only Weak Clients Yue Niu, Saurav Prakash, Souvik Kundu, Sunwoo Lee, Salman Avestimehr

TMLR 2023 Revisiting Sparsity Hunting in Federated Learning: Why Does Sparsity Consensus Matter? Sara Babakniya, Souvik Kundu, Saurav Prakash, Yue Niu, Salman Avestimehr

NeurIPSW 2023 SLoRA: Federated Parameter Efficient Fine-Tuning of Language Models Sara Babakniya, Ahmed Roushdy Elkordy, Yahya H. Ezzeldin, Qingfeng Liu, Kee-Bong Song, Mostafa EL-Khamy, Salman Avestimehr

ICLRW 2023 Secure Federated Learning Against Model Poisoning Attacks via Client Filtering Duygu Nur Yaldiz, Tuo Zhang, Salman Avestimehr

CVPR 2023 The Resource Problem of Using Linear Layer Leakage Attack in Federated Learning Joshua C. Zhao, Ahmed Roushdy Elkordy, Atul Sharma, Yahya H. Ezzeldin, Salman Avestimehr, Saurabh Bagchi

CVPRW 2023 TimelyFL: Heterogeneity-Aware Asynchronous Federated Learning with Adaptive Partial Training Tuo Zhang, Lei Gao, Sunwoo Lee, Mi Zhang, Salman Avestimehr

TMLR 2023 mL-BFGS: A Momentum-Based L-BFGS for Distributed Large-Scale Neural Network Optimization Yue Niu, Zalan Fabian, Sunwoo Lee, Mahdi Soltanolkotabi, Salman Avestimehr

NeurIPS 2022 FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings 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 Teleńczuk, Shadi Albarqouni, Salman Avestimehr, Aurélien Bellet, Aymeric Dieuleveut, Martin Jaggi, Sai Praneeth Karimireddy, Marco Lorenzi, Giovanni Neglia, Marc Tommasi, Mathieu Andreux

NeurIPSW 2022 Federated Learning of Large Models at the Edge via Principal Sub-Model Training Yue Niu, Saurav Prakash, Souvik Kundu, Sunwoo Lee, Salman Avestimehr

NeurIPSW 2022 Federated Sparse Training: Lottery Aware Model Compression for Resource Constrained Edge Sara Babakniya, Souvik Kundu, Saurav Prakash, Yue Niu, Salman Avestimehr

NeurIPSW 2022 LightVeriFL: Lightweight and Verifiable Secure Federated Learning Baturalp Buyukates, Jinhyun So, Hessam Mahdavifar, Salman Avestimehr

NeurIPS 2022 Self-Aware Personalized Federated Learning Huili Chen, Jie Ding, Eric W. Tramel, Shuang Wu, Anit Kumar Sahu, Salman Avestimehr, Tao Zhang

AAAI 2022 SpreadGNN: Decentralized Multi-Task Federated Learning for Graph Neural Networks on Molecular Data Chaoyang He, Emir Ceyani, Keshav Balasubramanian, Murali Annavaram, Salman Avestimehr

NeurIPSW 2021 Basil: A Fast and Byzantine-Resilient Approach for Decentralized Training Ahmed Roushdy Elkordy, Saurav Prakash, Salman Avestimehr

ICML 2021 PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-Scale Models Chaoyang He, Shen Li, Mahdi Soltanolkotabi, Salman Avestimehr

NeurIPS 2020 A Scalable Approach for Privacy-Preserving Collaborative Machine Learning Jinhyun So, Basak Guler, Salman Avestimehr

NeurIPS 2020 Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge Chaoyang He, Murali Annavaram, Salman Avestimehr

NeurIPS 2020 Minimax Lower Bounds for Transfer Learning with Linear and One-Hidden Layer Neural Networks Mohammadreza Mousavi Kalan, Zalan Fabian, Salman Avestimehr, Mahdi Soltanolkotabi

NeurIPS 2018 GradiVeQ: Vector Quantization for Bandwidth-Efficient Gradient Aggregation in Distributed CNN Training Mingchao Yu, Zhifeng Lin, Krishna Narra, Songze Li, Youjie Li, Nam Sung Kim, Alexander Schwing, Murali Annavaram, Salman Avestimehr

NeurIPS 2018 Pipe-SGD: A Decentralized Pipelined SGD Framework for Distributed Deep Net Training Youjie Li, Mingchao Yu, Songze Li, Salman Avestimehr, Nam Sung Kim, Alexander Schwing

NeurIPS 2017 Polynomial Codes: An Optimal Design for High-Dimensional Coded Matrix Multiplication Qian Yu, Mohammad Maddah-Ali, Salman Avestimehr