InfoQ

Meta's Optimization Platform Ax 1.0 Streamlines LLM and System Optimization

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
Frontiers

Research on intelligent fracturing parameter optimization method based on deep learning and construction curve feature extraction

Introduction: Optimizing fracturing parameters under multi-factor, complex conditions remains challenging in low-permeability reservoirs. Methods: We extract stage-aware construction-curve features, ...
IEEE

Automatic Calibration of Ranked Nodes in Bayesian Networks Using Genetic Algorithms

Bayesian Networks (BNs) are probabilistic models widely used for decision-making under uncertainty, relying on Conditional Probability Tables (CPTs) to represent the dependencies among variables.
C&EN

Enhancement of Li-Ion Battery Cathode Performance via Bayesian and Genetic Algorithm Optimization: Experimental and Numerical Analysis

Department of Intelligent Energy and Industry, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea Department of Intelligent Energy and Industry, Chung-Ang University, 84 ...
Frontiers

Benchmarking of feed-forward neural network models for genomic prediction of quantitative traits in pigs

Artificial neural networks are machine learning models that have been applied to various genomic problems, with the ability to learn non-linear relationships and model high-dimensional data. These ...
Scientific Research Publishing

Yu, T. and Zhu, H. (2020) Hyper-Parameter Optimization: A Review of Algorithms and Applications. arXiv: 2003.05689.

ABSTRACT: The advent of the internet, as we all know, has brought about a significant change in human interaction and business operations around the world; yet, this evolution has also been marked by ...