IEEE

Sample-Efficient Modeling and Optimization of High-Dimensional Semiconductor Processes Using Output-Augmented Gaussian Process Regression and Dynamic Bayesian Optimization

Abstract: Semiconductor process modeling in early stages of process development is challenging due to limited availability of the data, high dimensionality of inputs and outputs, and ...
EurekAlert!

How an algorithm is curing 3D printing’s cracking problem

In International Journal of Extreme Manufacturing, researchers at the University of Science and Technology Beijing developed ...
IGN

Capcom Drops Monster Hunter Wilds Patch That Aims to Improve Optimization for 'Steam-Specific Processes' and Address Long-Standing PC Issues

Capcom has dropped another Monster Hunter Wilds patch that aims to improve optimization for "Steam-specific processes" and address the game's long-standing PC issues. "After receiving user reports, ...
Frontiers

EcoBOT: an AI/ML enabled automated phenotyping capability for model plants

Advances in automation and AI/ML offer new opportunities for plant science, including design, modeling, and analysis. This study aimed to develop an automated platform for researching small model ...
eLife

Learning sequence-function relationships with scalable, interpretable Gaussian processes

This important work introduces a family of interpretable Gaussian process models that allows us to learn and model sequence-function relationships in biomolecules. These models are applied to three ...
Scientific Research Publishing

Snoek, J., Larochelle, H. and Adams, R.P. (2012) Practical Bayesian Optimization of Machine Learning Algorithms. Advances in Neural Information Processing Systems, Vol. 5, 2951 ...

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...
IEEE

Automated Class Imbalance Learning via Few-shot Multi-Objective Bayesian Optimization with Deep Kernel Gaussian Processes

Abstract: Automated Class Imbalance Learning (AutoCIL) is an emerging paradigm that leverages Combined Algorithm Selection and Hyperparameter Optimization (CASH) to automate the configuration of ...