Open Heart

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...
www.cs.cmu.edu

On Noisy Evaluation in Federated Hyperparameter Tuning

Hyperparameter tuning is critical to the success of cross-device federated learning applications. Unfortunately, federated networks face issues of scale, heterogeneity, and privacy; addressing these ...
Scientific Research Publishing

Li, L., Jamieson, K., DeSalvo, G., Rostamizadeh, A. and Talwalkar, A. (2020) Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization. Journal of Machine ...

ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...
IEEE

Federated Learning With Automated Dual-Level Hyperparameter Tuning

Abstract: Federated Learning (FL) is a decentralized machine learning (ML) approach where multiple clients collaboratively train a shared model over several update rounds without exchanging local data ...
IEEE

Enhancing Liver Cirrhosis Diagnosis Using Machine Learning With Explainable AI and Cross-Validated Hyperparameter Tuning Techniques

Abstract: Cirrhosis is a form of Chronic Liver Disease (CLD) resulting from sustained liver damage from several causes, including viral infection, autoimmune disorders, cholestatic and metabolic ...
GitHub

index.md

Hyperparameter tuning is crucial in machine learning as it significantly impacts model performance. One commonly used method for tuning hyperparameters is Random Search. This approach involves ...
GitHub

hyperparameter-tuning

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
Scientific Research Publishing

Elgeldawi, E., Sayed, A., Galal, A.R. and Zaki, A.M. (2021) Hyperparameter Tuning for Machine Learning Algorithms Used for Arabic Sentiment Analysis. Informatics, 8, Article 79.

ABSTRACT: Traditional methods for selecting models in experimental data analysis are susceptible to researcher bias, hindering exploration of alternative explanations and potentially leading to ...