Scientific Research Publishing

Yang, L. and Shami, A. (2020) On Hyperparameter Optimization of Machine Learning Algorithms: Theory and Practice. Neurocomputing, 415, 295-316.

ABSTRACT: This paper focuses on the use of YOLOv12 for the early detection of Sexually Transmitted Infections, which are a global public health challenge. YOLOv12 is a deep-learning model released on ...
Scientific Research Publishing

Kiran, M. and Ozyildirim, M. (2022) Hyperparameter Tuning for Deep Reinforcement Learning Applications. arXiv: 2201.11182.

ABSTRACT: The integration of artificial intelligence into the development and production of mechatronic products offers a substantial opportunity to enhance efficiency, adaptability, and system ...
IEEE

Regression-Based Hyperparameter Learning for Support Vector Machines

Abstract: Unification of classification and regression is a major challenge in machine learning and has attracted increasing attentions from researchers. In this article, we present a new idea for ...
marktechpost

Meet Optuna: An Automatic Hyperparameter Optimization Software Framework Designed for Machine Learning

In machine learning, finding the perfect settings for a model to work at its best can be like looking for a needle in a haystack. This process, known as hyperparameter optimization, involves tweaking ...
leewayhertz

Optimize to actualize: The impact of hyperparameter tuning on AI

In machine learning, algorithms harness the power to unearth hidden insights and predictions from within data. Central to the effectiveness of these algorithms are hyperparameters, which can be ...