Abstract: Hybrid loss minimization algorithms in electrical drives combine the benefits of search-based and model-based approaches to deliver fast and robust dynamic responses. This article presents a ...

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: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...

Python has become one of the most popular programming languages out there, particularly for beginners and those new to the hacker/maker world. Unfortunately, while it’s easy to get something up and ...

BLOOM (TAMPA)- On this episode of Bloom Health Club presented by Monticciolo Family & Sedation Dentistry, host Gayle Guyardo welcomes Brain Injury Expert Dr. Joseph Dituri, also known as Dr. Deep Sea, ...

Function secret sharing (FSS) is a secret sharing technique for functions in a specific function class, mainly including distributed point function (DPF) and distributed comparison function (DCF). As ...

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. Massie: Judges rejected 'lie' about Epstein files ICC ...

ORLANDO, Fla. — Steering clinicians toward a cascade approach for thyroid function testing cut unnecessary orders by a monthly average of 15% and concurrent orders by 19% per month, according to ...

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 ...

Check the paper on ArXiv: FastBDT: A speed-optimized and cache-friendly implementation of stochastic gradient-boosted decision trees for multivariate classification Stochastic gradient-boosted ...