Optimization lies at the heart of deep learning, driving neural networks to discover patterns in vast and complex datasets. Early approaches relied on batch gradient descent, which computes exact ...

This technical paper titled “DNN-Opt: An RL Inspired Optimization for Analog Circuit Sizing using Deep Neural Networks” is co-authored from researchers at The University of Texas at Austin, Intel, ...

A deep reinforcement learning framework optimizes silicon-based photonic crystal fiber modulators, achieving ultra-low ...

AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...