Semiconductor Engineering

Parallel Implementation Of Nonlinear Functions Using An Optical Processor (UCLA)

A new technical paper titled “Massively parallel and universal approximation of nonlinear functions using diffractive ...
Tech Xplore on MSN

Optical system uses diffractive processors to achieve large-scale nonlinear computation

Researchers at the University of California, Los Angeles (UCLA) have developed an optical computing framework that performs ...
EurekAlert!

Massively parallel implementation of nonlinear functions using an optical processor

UCLA researchers demonstrate diffractive optical processors as universal nonlinear function approximators using linear ...
IEEE

Gradient Flow Approximations in Temporal Difference Learning

Abstract: We consider the continuous-time temporal difference (TD) learning dynamics with nonlinear value function approximations, where there is a slim understanding of the convergence properties in ...
IEEE

Piecewise-Linear Approximation of Self-Attention and Its Accuracy-Aware Training for Area-Efficient Vision Transformer Inference Accelerator

Abstract: Vision Transformer (ViT) is a neural network model specialized for image processing, introduced in 2021. The key feature of ViT is self-attention, which allows it to capture a wide range of ...