TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...
AZoRobotics on MSN

Neuron-driven control could redefine how soft robots handle the unexpected

This study presents a bio-inspired control framework for soft robots, enhancing tracking accuracy by over 44% under ...
IEEE

Learning Error Refinement in Stochastic Gradient Descent-Based Latent Factor Analysis via Diversified PID Controllers

Abstract: In Big Data-based applications, high-dimensional and incomplete (HDI) data are frequently used to represent the complicated interactions among numerous nodes. A stochastic gradient descent ...
IEEE

AlphaGrad: Normalized Gradient Descent for Adaptive Multi-Loss Functions in EEG-Based Motor Imagery Classification

Abstract: In this study, we propose AlphaGrad, a novel adaptive loss blending strategy for optimizing multi-task learning (MTL) models in motor imagery (MI)-based electroencephalography (EEG) ...