Learn how airline gate upgrades really work, who gets bumped to first class first, and the factors that determine ...

Applied Materials (AMAT) held a master class event this week, and much of the focus was on the company's positioning in ...

Abstract: In this paper, a new method is presented to compute the 2-adic complexity of pseudo-random sequences. With this method, the 2-adic complexities of all the known sequences with ideal 2-level ...

Many industrial applications in the automotive, automation, appliance, or medical sectors require power supplies that comply with functional safety standards. If the input voltage of such a power ...

This study introduces a sophisticated intelligent predictive maintenance system for industrial conveyor belts powered by a random forest machine learning model. The random forest model was evaluated ...

Space complexity of machine learning algorithms is the amount of memory or storage an algorithm requires for its successful execution. This becomes one of the important metrics of concern since it ...

Lecture 01: Overview of the course Review: Arora--Barak Chapters 1 (except 1.7), 2, and 4 Lecture 02: Hierarchy theorems: time, space, and nondeterministic versions Reading: Arora--Barak Chapters 3.1, ...

Abstract: Non-exemplar class-incremental learning refers to continual classifying of new and old classes without storing samples of old classes. Since only new class samples are available, ...

Decision Trees theory is a method used in machine learning and data analysis that allows building decision-making models with tree-shaped hierarchy. In each node of the tree, a certain criterion is ...

Machine learning and deep learning have been widely embraced, and even more widely misunderstood. In this article, I’ll step back and explain both machine learning and deep learning in basic terms, ...