WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning

WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning BEIJING, Jan. 05, 2026––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the ...
Visual Studio Magazine

Kernel Ridge Regression with Cholesky Inverse Training Using C#

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses the kernel matrix inverse (Cholesky ...
Visual Studio Magazine

Kernel Ridge Regression with Stochastic Gradient Descent Training Using JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses stochastic gradient descent, one of two ...
Yale Environment 360

SoFiE Financial Machine Learning Summer School

The Society for Financial Econometrics (SoFiE) Summer School is an annual week-long research-based course for PhD students, new faculty, and professionals in financial econometrics. For the first two ...
Frontiers

A risk prediction model for poor joint function recovery after ankle fracture surgery based on interpretable machine learning

Objective: Currently, there is no individualized prediction model for joint function recovery after ankle fracture surgery. This study aims to develop a prediction model for poor recovery following ...
News Medical

Machine learning identifies key lifestyle factors for healthy brain function

A new study offers insight into the health and lifestyle indicators - including diet, physical activity and weight - that align most closely with healthy brain function across the lifespan. The study ...
Frontiers

Development and validation of a machine learning model based on multiple kernel for predicting the recurrence risk of Budd-Chiari syndrome

Background: Budd-Chiari syndrome (BCS) is a rare global condition with high recurrence rates. Existing prognostic scoring models demonstrate limited predictive efficacy for BCS recurrence. This study ...
Hosted on MSN

Linear Regression Cost Function | Machine Learning | Explained Simply

Learn what is Linear Regression Cost Function in Machine Learning and how it is used. Linear Regression Cost function in Machine Learning is "error" representation between actual value and model ...
C&EN

Applying Gaussian Process Machine Learning and Modern Probabilistic Programming to Satellite Data to Infer CO

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Satellite data provides essential insights into the spatiotemporal distribution of CO ...
IEEE

Benchmarking Quantum Machine Learning Kernel Training for Classification Tasks

Abstract: Quantum-enhanced machine learning is a rapidly evolving field that aims to leverage the unique properties of quantum mechanics to enhance classical machine learning. However, the practical ...
IEEE

Multi-Kernel Learning for Heterogeneous Data

Abstract: Multi-kernel learning is an excellent machine learning algorithm widely used in various learning tasks such as classification and regression. Traditional kernel methods mainly focus on ...