(2026) AI Assisted Material Selection Framework for Corrosion Resistant Steels in Onshore Oil and Gas Pipelines. Open Journal ...

Abstract: Hyperparameter optimization plays a pivotal role in the reliability and generalization of machine-learning models for software quality prediction. This paper presents a comparative ...

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 ...

1 Aviation Service Institute,Jiangsu Aviation Technical College, Zhenjiang, China 2 Ocean College, Jiangsu University of Science and Technology, Zhenjiang, China Reliable forecasting of air cargo ...

Abstract: Automatic performance tuning (auto-tuning) is widely used to optimize performance-critical applications across many scientific domains by finding the best program variant among many choices.

I've been working with the code and noticed that the current model (RandomForestRegressor) could benefit from hyperparameter tuning. The current setup uses default parameters, which may not be optimal ...

Rotary Positional Embedding (RoPE) is a widely used technique in Transformers, influenced by the hyperparameter theta (θ). However, the impact of varying *fixed* theta values, especially the trade-off ...

Opinions expressed by Entrepreneur contributors are their own. AI tools like ChatGPT are becoming key referral sources for service-based businesses. Learn how to optimize your online presence so AI ...

AI search tools are on the rise, but SEO fundamentals remain critical. Learn how the two intersect and what it means for your strategy. The explosive rise of ChatGPT and other generative AI tools has ...

Add native support for Bayesian hyperparameter optimization directly within MLflow, eliminating the need for external libraries like Optuna or Hyperopt. This feature would provide a deeply integrated ...