pSConv: A Pre-defined S parse Kernel Based Convolution for Deep CNNs. - Souvik Kundu 002; Saurav Prakash; Haleh Akrami; Peter A. Beerel; Keith M. Chugg (Allerton, 2019)

Coded Federated Learning. - Sagar Dhakal; Saurav Prakash; Yair Yona; Shilpa Talwar; Nageen Himayat (GLOBECOM Workshops, 2019)

Tree Gradient Coding. - Amirhossein Reisizadeh; Saurav Prakash; Ramtin Pedarsani; Amir Salman Avestimehr (ISIT, 2019)

Coded Computing for Distributed Machine Learning in Wireless Edge Network. - Sagar Dhakal; Saurav Prakash; Yair Yona; Shilpa Talwar; Nageen Himayat (VTC Fall, 2019)

A Pre-defined Sparse Kernel Based Convolution for Deep CNNs. - Souvik Kundu 002; Saurav Prakash; Haleh Akrami; Peter A. Beerel; Keith M. Chugg (CoRR, 2019)

Coded Computation Over Heterogeneous Clusters. - Amirhossein Reisizadeh; Saurav Prakash; Ramtin Pedarsani; Amir Salman Avestimehr (IEEE Trans. Inf. Theory, 2019)

Hierarchical Coded Gradient Aggregation for Learning at the Edge. - Saurav Prakash; Amirhossein Reisizadeh; Ramtin Pedarsani; Amir Salman Avestimehr (ISIT, 2020)

Coded Computing for Federated Learning at the Edge. - Saurav Prakash; Sagar Dhakal; Mustafa Riza Akdeniz; Amir Salman Avestimehr; Nageen Himayat (CoRR, 2020)

Mitigating Byzantine Attacks in Federated Learning. - Saurav Prakash; Amir Salman Avestimehr (CoRR, 2020)

Coded Computing for Distributed Graph Analytics. - Saurav Prakash; Amirhossein Reisizadeh; Ramtin Pedarsani; Amir Salman Avestimehr (IEEE Trans. Inf. Theory, 2020)

Coded Computing for Low-Latency Federated Learning Over Wireless Edge Networks. - Saurav Prakash; Sagar Dhakal; Mustafa Riza Akdeniz; Yair Yona; Shilpa Talwar; Salman Avestimehr; Nageen Himayat (IEEE J. Sel. Areas Commun., 2021)

Federated Sparse Training: Lottery Aware Model Compression for Resource Constrained Edge. - Sara Babakniya; Souvik Kundu 002; Saurav Prakash; Yue Niu; Salman Avestimehr (CoRR, 2022)

Federated Learning of Large Models at the Edge via Principal Sub-Model Training. - Yue Niu; Saurav Prakash; Souvik Kundu 002; Sunwoo Lee 001; Salman Avestimehr (CoRR, 2022)

Basil: A Fast and Byzantine-Resilient Approach for Decentralized Training. - Ahmed Roushdy Elkordy; Saurav Prakash; Salman Avestimehr (IEEE J. Sel. Areas Commun., 2022)

CodedReduce: A Fast and Robust Framework for Gradient Aggregation in Distributed Learning. - Amirhossein Reisizadeh; Saurav Prakash; Ramtin Pedarsani; Amir Salman Avestimehr (IEEE/ACM Trans. Netw., 2022)

Machine Unlearning of Federated Clusters. - Chao Pan 003; Jin Sima; Saurav Prakash; Vishal Rana; Olgica Milenkovic (ICLR, 2023)

Revisiting Sparsity Hunting in Federated Learning: Why does Sparsity Consensus Matter? - Sara Babakniya; Souvik Kundu 002; Saurav Prakash; Yue Niu; Salman Avestimehr (Trans. Mach. Learn. Res., 2023)

Overcoming Resource Constraints in Federated Learning: Large Models Can Be Trained with only Weak Clients. - Yue Niu; Saurav Prakash; Souvik Kundu 002; Sunwoo Lee 001; Salman Avestimehr (Trans. Mach. Learn. Res., 2023)

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

ATP: Enabling Fast LLM Serving via Attention on Top Principal Keys. - Yue Niu; Saurav Prakash; Salman Avestimehr (CoRR, 2024)

Federated Classification in Hyperbolic Spaces via Secure Aggregation of Convex Hulls. - Saurav Prakash; Jin Sima; Chao Pan 003; Eli Chien; Olgica Milenkovic (Trans. Mach. Learn. Res., 2024)

Embracing Federated Learning: Enabling Weak Client Participation via Partial Model Training. - Sunwoo Lee 001; Tuo Zhang; Saurav Prakash; Yue Niu; Salman Avestimehr (IEEE Trans. Mob. Comput., 2024)