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Temporal credit assignment for one-shot learning utilizing a phase transition material
Design of hardware based on biological principles of neuronal computation and plasticity in the brain is a leading approach to realizing energy- and sample-efficient artificial intelligence and learning machines.
Multi-Task Fusion via Reinforcement Learning for Long-Term User Satisfaction in Recommender Systems
The mainstream RS ranking framework is composed of two parts: a Multi-Task Learning model (MTL) that predicts various user feedback, i. e., clicks, likes, sharings, and a Multi-Task Fusion model (MTF) that combines the multi-task outputs into one final ranking score with respect to user satisfaction.
IOCA: High-Speed I/O-Aware LLC Management for Network-Centric Multi-Tenant Platform
In this paper, we argue that besides CPU cores, high-speed network I/O is also important for LLC management.
Hardware Architecture Operating Systems
