Multi-objective hyperparameter optimization in machine learning—An overview

F Karl, T Pielok, J Moosbauer, F Pfisterer… - ACM Transactions on …, 2023‏ - dl.acm.org
Hyperparameter optimization constitutes a large part of typical modern machine learning
(ML) workflows. This arises from the fact that ML methods and corresponding preprocessing …

[HTML][HTML] Hyperparameter optimization and combined data sampling techniques in machine learning for customer churn prediction: a comparative analysis

M Imani, HR Arabnia - Technologies, 2023‏ - mdpi.com
This paper explores the application of various machine learning techniques for predicting
customer churn in the telecommunications sector. We utilized a publicly accessible dataset …

Advances in neural rendering

A Tewari, J Thies, B Mildenhall… - Computer Graphics …, 2022‏ - Wiley Online Library
Synthesizing photo‐realistic images and videos is at the heart of computer graphics and has
been the focus of decades of research. Traditionally, synthetic images of a scene are …

On the analyses of medical images using traditional machine learning techniques and convolutional neural networks

S Iqbal, A N. Qureshi, J Li, T Mahmood - Archives of Computational …, 2023‏ - Springer
Convolutional neural network (CNN) has shown dissuasive accomplishment on different
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …