Learn how gradient descent really works by building it step by step in Python. No libraries, no shortcuts—just pure math and ...

Learn how to implement SGD with momentum from scratch in Python—boost your optimization skills for deep learning.

Abstract: The gradient descent bit-flipping with momentum (GDBF-w/M) and probabilistic GDBF-w/M (PGDBF-w/M) algorithms significantly improve the decoding performance of the bit-flipping (BF) algorithm ...

Abstract: Distributed gradient descent algorithms have come to the fore in modern machine learning, especially in parallelizing the handling of large datasets that are distributed across several ...

Stochastic gradient descent (SGD) provides a scalable way to compute parameter estimates in applications involving large-scale data or streaming data. As an alternative version, averaged implicit SGD ...

Ever wondered how social media platforms decide how to fill our feeds? They use algorithms, of course, but how do these algorithms work? A series of corporate leaks over the past few years provides a ...

Nearly 30 years after it first hit theaters, Paul W.S. Anderson's Event Horizon is finally getting a prequel. IDW Publishing has revealed Event Horizon: Dark Descent, a five-issue comic book series ...

ABSTRACT: In this paper, we investigate the convergence of the generalized Bregman alternating direction method of multipliers (ADMM) for solving nonconvex separable problems with linear constraints.