The New Yorker

The Case That A.I. Is Thinking

Dario Amodei, the C.E.O. of the artificial-intelligence company Anthropic, has been predicting that an A.I. “smarter than a Nobel Prize winner” in such fields as biology, math, engineering, and ...
IEEE

A Filtered Gradient Descent Clustering Method to Recover Communities in Attributed Networks

Abstract: An attributed network is a network in which in addition to the network structure each node is associated with a set of attributes. Community detection in such networks involves recovering ...
Hosted on MSN

Logistic Regression Explained with Gradient Descent — Full Derivation Made Easy!

Struggling to understand how logistic regression works with gradient descent? This video breaks down the full mathematical derivation step-by-step, so you can truly grasp this core machine learning ...
IEEE

Partial Discharge Location With Gradient-Descent Total Least-Squares Euclidean Direction Search Algorithm for Cable Systems

Abstract: Based on the total least-squares (TLS) model, the gradient-descent TLS Euclidean direction search (GD-TLS-EDS) algorithm is proposed when both input and output signals are corrupted by ...
Scientific Research Publishing

A Comparative Study of Optimization Techniques on the Rosenbrock Function ()

1 Department of Mathematics, University of Ndjamena, Ndjamena, Tchad. 2 Department of Mathematics and Computer Science, University of Cheikh. A. Diop, Dakar, Senegal. In the evolving landscape of ...
insideHPC

RMSprop Optimization Algorithm for Gradient Descent with Neural Networks

A big part of AI and Deep Learning these days is the tuning/optimizing of the algorithms for speed and accuracy. Much of today’s deep learning algorithms involve the use of the gradient descent ...