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From the 2 of 52 linked papers with an AI index.
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cs.LG2026
SGD-Based Knowledge Distillation with Bayesian Teachers: Theory and Guidelines
Itai Morad, Nir Shlezinger, Yonina C. Eldar
Knowledge Distillation (KD) is a central paradigm for transferring knowledge from a large teacher network to a typically smaller student model, often by leveraging soft probabilist…
cs.LG2026
Deep Unfolding: Recent Developments, Theory, and Design Guidelines
Nir Shlezinger, Santiago Segarra, Yi Zhang +4
Optimization methods play a central role in signal processing, serving as the mathematical foundation for inference, estimation, and control. While classical iterative optimization…
cs.LG2026
Adaptive Deadline and Batch Layered Synchronized Federated Learning
Asaf Goren, Natalie Lang, Nir Shlezinger +1
Federated learning (FL) enables collaborative model training across distributed edge devices while preserving data privacy, and typically operates in a round-based synchronous mann…