2 papers
cs.LG2026
Robust Federated Learning Under Real-World Client Churn
Dhruv Garg, Neha Lakhani, Debopam Sanyal +3
Federated Learning (FL) enables training shared models on private, on-device data, but production deployments remain constrained to slow, multi-day refresh cycles due to the comple…
cs.DC2023
SuperServe: Fine-Grained Inference Serving for Unpredictable Workloads
Alind Khare, Dhruv Garg, Sukrit Kalra +3
The increasing deployment of ML models on the critical path of production applications in both datacenter and the edge requires ML inference serving systems to serve these models u…