Key Takeaways -   To understand data science, one needs a lot of technical expertise along with business understanding. Generative AI, MLOps, and clou ...

Gradient descent has a fundamental limitation: on most real-world loss surfaces, it is inefficient. When the surface has uneven curvature—steep in one direction and flat in another, which is common in ...

As modern computing becomes limited by energy consumption, there is growing interest in physical computing paradigms that can operate closer to fundamental thermodynamic limits. Thermodynamic ...

Abstract: A fast gradient-descent (FGD) method is proposed for far-field pattern synthesis of large antenna arrays. Compared with conventional gradient-descent (GD) methods for pattern synthesis where ...

Abstract: In this article, we propose a maneuvering target tracking algorithm based on the sojourn-time-dependent semi-Markov variable structure interacting multiple model (STDM-VSIMM) filter. Due to ...

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.

The success of deep learning contrasts with its limited understanding. One example is stochastic gradient descent, the main algorithm used to train neural networks ...

This article illustrates how to build, in less than 5 minutes, a simple linear regression model with gradient descent. The goal is to predict a dependent variable (y) from an independent variable (X).

Tim is an Australian Senior Editor based in Germany who has been passionate about video games since he first picked up a PlayStation 1 controller to play Crash Bandicoot as a kid. He started out with ...