Science

Few-shot neuromorphic vision in a nonlinear photonic network laser

With the growing prevalence of artificial intelligence (AI), demand increases for hardware that mimics the brain’s ability to ...

AI suggests new physics experiments that could outperform human-designed setups

Research means asking questions of the universe. For centuries, clever minds have advanced science by devising ingenious ...

Just like a fruit fly, a new algorithm never forgets old scents

Feed the network new odors a couple at a time—a stress test for catastrophic forgetting—and Spi-Fly barely blinks, holding ...

PACMAN AI framework for controlling fusion systems safely makes key decisions in milliseconds

Inside some fusion energy systems, particles hotter than the core of the sun can become unruly in a few thousandths of a second, far faster than any human operator can react. A new software framework ...
pv magazine International

Machine learning improves irradiance prediction in bifacial PV systems

A Selçuk University researcher has compared six machine learning algorithms for predicting front- and rear-side ...
quantumzeitgeist

Researchers Build Quantum Multi-Label k-Nearest Neighbor Algorithm

Researchers at the College of Computer Science and Electronic Engineering, Hunan University, are addressing a critical bottleneck in machine learning: the increasing time demands of the multi-label ...
Frontiers

Improving the estimation accuracy of rice leaf protein nitrogen using data augmentation, explainable machine learning, and UAV hyperspectral imagery

Efficiently estimating the protein nitrogen content of rice leaves (LPN) is crucial for monitoring the nutritional health of rice and guiding precision fertilization based on requirements. Unmanned ...
International Monetary Fund

GDP Nowcasting Performance of Traditional Econometric Models vs Machine-Learning Algorithms: Simulation and Case Studies

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...
Scientific Research Publishing

Larose, D.T. and Larose, C.D. (2014) k-Nearest Neighbor Algorithm.

ABSTRACT: This paper proposes a structured data prediction method based on Large Language Models with In-Context Learning (LLM-ICL). The method designs sample selection strategies to choose samples ...
EurekAlert!

Transforming acute exacerbations of chronic obstructivepulmonary disease (AECOPD) risk assessment: Amulti-algorithm machine learning approach for preciseclinical phenotyping

The workflow encompasses patient datacollection and screening, univariate regression analysis for initial variable selection, systematic comparison of 91 machine learning models,selection and ...
letsdatascience

K-Nearest Neighbors: Distance, Scaling, and Choosing K

"You are the average of the five people you spend the most time with." Jim Rohn's famous line is not just life advice; it is the entire operating principle behind K-Nearest Neighbors (KNN). The ...