Interpretable machine learning to accelerate nanocatalyst discovery

A fast and accurate surrogate model screens over 10,000 possible metal-oxide supports for a platinum nanocatalyst to prevent sintering under high temperatures.
IEEE

Application of Evolutionary Algorithms to Enhance the Efficiency of Neural Networks and Machine Learning Algorithms

Abstract: This study examines approaches to hyperparameter optimization in machine learning and deep learning systems using genetic algorithms. Today, the success of neural networks and machine ...
Journal of Medical Internet Research

Optimizing Initial Vancomycin Dosing in Hospitalized Patients Using Machine Learning Approach for Enhanced Therapeutic Outcomes: Algorithm Development and Validation Study

Objective: This study aimed to develop and evaluate a machine learning (ML)–based algorithm to predict whether an initial vancomycin dose falls within the therapeutic range of the 24-hour area under ...
IEEE

MPDA: A Massively Parallel Learning and Dependency-Aware Scheduling Algorithm for Data Processing Clusters

Abstract: In the era of large-scale machine learning, large-scale clusters are extensively used for data processing jobs. However, the state-of-the-art heuristic-based and Deep Reinforcement Learning ...