2 papers
cs.LG2026
PAC-Bayes Beyond Parameter Space: Behavioral Equivalence, Z-Information, and Exact Complexity Decomposition
Vasant G. Honavar, Satish Kumar Keshri, Neil Ashtekar +1
PAC-Bayes theory provides generalization guarantees by controlling the Kullback--Leibler (KL) divergence between posterior and prior distributions over a chosen hypothesis represen…
cs.LG2025
On the Convergence of Continual Federated Learning Using Incrementally Aggregated Gradients
Satish Kumar Keshri, Nazreen Shah, Ranjitha Prasad
The holy grail of machine learning is to enable Continual Federated Learning (CFL) to enhance the efficiency, privacy, and scalability of AI systems while learning from streaming d…