Ayyoun is a staff writer who loves all things gaming and tech. His journey into the realm of gaming began with a PlayStation 1 but he chose PC as his platform of choice. With over 6 years of ...

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 ...

Learn how gradient descent really works by building it step by step in Python. No libraries, no shortcuts—just pure math and code made simple. LDS Church's presidency reveal sparks "hilarious" ...

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 ...

In the '8_sgd_vs_gd' folder, the 'gd_and_sgd.ipynb' file, there is a logic flaw in the Stochastic Gradient Descent code, Since for SGD, it uses 1 randomly selected ...

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 ...

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 ...

ABSTRACT: The development of artificial intelligence (AI), particularly deep learning, has made it possible to accelerate and improve the processing of data collected in different fields (commerce, ...