Adaptive Quantization of Model Updates for Communication-Efficient Federated Learning. - Divyansh Jhunjhunwala; Advait Gadhikar; Gauri Joshi; Yonina C. Eldar (ICASSP, 2021)

Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation. - Divyansh Jhunjhunwala; Ankur Mallick; Advait Gadhikar; Swanand Kadhe; Gauri Joshi (NeurIPS, 2021)

Fedvarp: Tackling the variance due to partial client participation in federated learning. - Divyansh Jhunjhunwala; Pranay Sharma; Aushim Nagarkatti; Gauri Joshi (UAI, 2022)

To Federate or Not To Federate: Incentivizing Client Participation in Federated Learning. - Yae Jee Cho; Divyansh Jhunjhunwala; Tian Li 005; Virginia Smith; Gauri Joshi (CoRR, 2022)

FedExP: Speeding Up Federated Averaging via Extrapolation. - Divyansh Jhunjhunwala; Shiqiang Wang 001; Gauri Joshi (ICLR, 2023)

FedFisher: Leveraging Fisher Information for One-Shot Federated Learning. - Divyansh Jhunjhunwala; Shiqiang Wang 001; Gauri Joshi (AISTATS, 2024)

Erasure Coded Neural Network Inference via Fisher Averaging. - Divyansh Jhunjhunwala; Neharika Jali; Gauri Joshi; Shiqiang Wang 001 (ISIT, 2024)

Maximizing Global Model Appeal in Federated Learning. - Yae Jee Cho; Divyansh Jhunjhunwala; Tian Li 005; Virginia Smith; Gauri Joshi (Trans. Mach. Learn. Res., 2024)

Initialization Matters: Unraveling the Impact of Pre-Training on Federated Learning. - Divyansh Jhunjhunwala; Pranay Sharma; Zheng Xu 002; Gauri Joshi (CoRR, 2025)

Navigating the Accuracy-Size Trade-Off with Flexible Model Merging. - Akash Balasaheb Dhasade; Divyansh Jhunjhunwala; Milos Vujasinovic; Gauri Joshi; Anne-Marie Kermarrec (CoRR, 2025)

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA. - Divyansh Jhunjhunwala; Arian Raje; Madan Ravi Ganesh; Chaithanya Kumar Mummadi; Chaoqun Dong; Jiawei Zhou; Wan-Yi Lin; Gauri Joshi; Zhenzhen Li (CoRR, 2025)

Ravan: Multi-Head Low-Rank Adaptation for Federated Fine-Tuning. - Arian Raje; Baris Askin; Divyansh Jhunjhunwala; Gauri Joshi (CoRR, 2025)