New AI optimization framework beats Claude Code and Codex by 2.5x on the same compute budget

Arbor separates strategy from execution using isolated git worktrees, so engineering teams can finally trace which ...
Tech Xplore

Combining lessons from ants and birds to improve AI

Combining ideas inspired by ant colonies and flocks of birds may hold the key to unlocking more effective artificial ...
Frontiers

Numerical foundations for scalable statistical and machine learning methods

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...
IEEE

A Novel Evolutionary Bayesian Optimization Algorithm Based on Decomposition for Expensive Constrained Multiobjective Optimization Problems

Abstract: This article proposes a novel constrained multiobjective evolutionary Bayesian optimization algorithm based on decomposition (named CMOEBO/D) for expensive constrained multiobjective ...
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 ...
GitHub

MultiObjective_MOEAD_EGO.m

% Q. Zhang, W. Liu, E. Tsang, and B. Virginas. Expensive Multiobjective % Optimization by MOEA/D with Gaussian Process model. IEEE Transactions on % Evolutionary ...
C&EN

Bayesian Optimization with Gaussian Processes Assisted by Deep Learning for Material Designs

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Developing novel materials drives significant breakthroughs ...