mccormick.northwestern.edu

COMP_SCI 496: Theory of Gradient-Based Optimization in ML

In this course, you’ll learn theoretical foundations of optimization methods used for training deep machine learning models. Why does gradient descent work? Specifically, what can we guarantee about ...
IEEE

EMO-CIM: An Input/Stationary-Data Similarity-Aware Computing-In-Memory Design for Variable Vector-Wise Computation in Edge Multi-Operator AI Acceleration

Abstract: We propose an edge multi-operator computing-in-memory design (EMO-CIM) that supports variable vector-wise multiply-and-accumulate (MAC) in CNN, Depthwise-Convolution (DW), and Attention ...
IEEE

A Gradient Vector Descent Strategy for Localizing Acoustic Emission Sources in Discontinuous Structures With a Hole

Abstract: The analysis of acoustic signals to localize acoustic emission (AE) sources has emerged as a kind of favored approach. Despite recent advances, the task of localizing AE sources such as ...