Deep-learning algorithms enhance mutation detection in cancer and RNA sequencing

Researchers from the Faculty of Engineering at The University of Hong Kong (HKU) have developed two innovative deep-learning ...

LearningMole Launches AI Literacy Initiative to Help Teachers and Parents Prepare Children for an AI-Enabled World

Educational platform announces expanded course programme addressing critical thinking, responsible use, and AI ...
EurekAlert!

RDHNet: Addressing rotational and permutational symmetries in continuous multi-agent systems

"Welcome to the world of RDHNet, a groundbreaking approach to multi-agent reinforcement learning (MARL) introduced by Dongzi Wang and colleagues from the College of Computer Science at the National ...
IEEE

A Lightweight Link Scheduling Algorithm in IWNs Based on Hybrid Graph Representation Learning

Abstract: In industrial wireless networks with resource-constrained and densely deployed devices, link scheduling is a challenging task. Traditional optimization methods have high computational ...
Scientific Research Publishing

Boosting Algorithm: An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ()

An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ...
Quanta Magazine

The Game Theory of How Algorithms Can Drive Up Prices

Imagine a town with two widget merchants. Customers prefer cheaper widgets, so the merchants must compete to set the lowest price. Unhappy with their meager profits, they meet one night in a ...
Frontiers

A dynamic multitask evolutionary algorithm for high-dimensional feature selection based on multi-indicator task construction and elite competition learning

High-dimensional data often contain noisy and redundant features, posing challenges for accurate and efficient feature selection. To address this, a dynamic multitask learning framework is proposed, ...
IEEE

Action-Based Contrastive Unsupervised Representations for Reinforcement Learning Toward Robotic Manipulation

Abstract: Although deep reinforcement learning (DRL) has made massive progress in policy learning, its reliance on a large number of real-world data samples presents a significant barrier to broader ...
Bloomberg L.P.

AI in Schools? A Chinese Entrepreneur Is Betting on Algorithms As Teachers

On a scorching July afternoon in Shanghai, dozens of Chinese students hunch over tablet screens, engrossed in English, math and physics lessons. Algorithms track every keystroke, and the seconds spent ...
Frontiers

Construction of a clinical prediction model for osteoporosis in asymptomatic elderly population based on machine learning algorithm

1 School of Information Engineering, Anhui University of Chinese Medicine, Hefei, China 2 School of Pharmaceutical Economics and Management, Anhui University of Chinese Medicine, Hefei, China ...
C&EN

A Machine-Learning-Algorithm Enhanced Multi-Functional Gas Sensor for Self-Humidity Compensation and Partial Discharge Detection

School of Health Science and Engineering, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, China ...
EurekAlert!

Neuromorphic devices and machine learning combine to make brain-like devices possible

As modern manufacturing increasingly relies on artificial intelligence (AI), automation, and real-time data processing, the need for faster and more energy-efficient computing systems has never been ...