JSTOR Daily

DISCRETE GRADIENT APPROACH TO STOCHASTIC DIFFERENTIAL EQUATIONS WITH A CONSERVED QUANTITY

SIAM Journal on Numerical Analysis, Vol. 49, No. 5/6 (2011), pp. 2017-2038 (22 pages) General autonomous stochastic differential equations (SDEs) driven by one-dimensional Brownian motion in the ...
Nature

Gradient Flows and Large Deviations in Stochastic Processes

The study of gradient flows and large deviations in stochastic processes forms a vital link between microscopic randomness and macroscopic determinism. By characterising how systems evolve in response ...
Visual Studio Magazine

Kernel Ridge Regression with Stochastic Gradient Descent Training Using C#

The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict a person's bank savings account balance based on their age, years of ...
EurekAlert!

Efficient stochastic parallel gradient descent training for on-chip optical processors

a) Conceptual diagram of the on-chip optical processor used for optical switching and channel decoder in an MDM optical communications system. (b) Integrated reconfigurable optical processor schematic ...
Semiconductor Engineering

Analog Accelerator For AI/ML Training Workloads Using Stochastic Gradient Descent (Imperial College London)

A new technical paper titled “Learning in Log-Domain: Subthreshold Analog AI Accelerator Based on Stochastic Gradient Descent” was published by researchers at Imperial College London. “The rapid ...