Optimizing RNA design with AI and an Ising machine: Encoding matters

RNA has emerged as one of the most promising molecules in modern medicine, enabling advances from mRNA vaccines and gene ...

Deep learning reveals nanoparticle shape from routine tracking analysis without new hardware

Researchers at the University of Tokyo and the Innovation Center of NanoMedicine (iCONM) have developed an artificial ...
IEEE

Optimizing Binary Decision Diagrams for Interpretable Machine Learning Classification

Abstract: Machine learning (ML) is ever more frequently used as a tool to aid decision making. The need to understand the decisions made by ML algorithms has sparked a renewed interest in explainable ...
Frontiers

A comparative analysis of binary and multi-class classification machine learning algorithms to detect current frailty status using the English longitudinal study of ageing (ELSA)

Physical frailty is a pressing public health issue that significantly increases the risk of disability, hospitalization, and mortality. Early and accurate detection of frailty is essential for timely ...
Visual Studio Magazine

Binary Classification Using LightGBM

Dr. James McCaffrey from Microsoft Research presents a full-code, step-by-step tutorial on using the LightGBM tree-based system to perform binary classification (predicting a discrete variable that ...
MIT Technology Review

How a simple circuit could offer an alternative to energy-intensive GPUs

The creative new approach could lead to more energy-efficient machine-learning hardware. On a table in his lab at the University of Pennsylvania, physicist Sam Dillavou has connected an array of ...
Visual Studio Magazine

Binary Classification Using a scikit Neural Network

Machine learning with neural networks is sometimes said to be part art and part science. Dr. James McCaffrey of Microsoft Research teaches both with a full-code, step-by-step tutorial. A binary ...
holisticai

Bias Mitigation Strategies and Techniques for Classification Tasks

The bias problem in classification tasks and the different strategies used for bias mitigation. How these strategies are grouped into categories and a brief introduction of the most representative ...