InfoWorld

The ‘toggle-away’ efficiencies: Cutting AI costs inside the training loop

You don't need the newest GPUs to save money on AI; simple tweaks like "smoke tests" and fixing data bottlenecks can slash ...

Humans Win By Latest ChatGPT Changes Reducing Teaser-Phrasing So That AI Won’t Be So Annoyingly Click-Baity

Many LLMs use teaser-phrasing to get users to keep going in a conversation. OpenAI says they are reducing this in ChatGPT.
GitHub

BONNI: Bayesian Optimization via Neural Network surrogates and Interior Point Optimization

BONNI optimizes any black box function WITH gradient information. Especially in optimizations with many degree of freedom, gradient-information increases optimization speed. In the image, the ...
Hosted on MSN

RMSProp optimization from scratch in Python

Understand and implement the RMSProp optimization algorithm in Python. Essential for training deep neural networks efficiently. #RMSProp #Optimization #DeepLearning Denmark facing "decisive moment" ...
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 ...
C&EN

Autonomous Robotic Mechanical Exfoliation of Two-Dimensional Semiconductors Combined with Bayesian Optimization

State Key Laboratory of Tribology in Advanced Equipment, Tsinghua University, Beijing 100084, China State Key Laboratory of Clean and Efficient Turbomachinery Power Equipment, Department of Mechanical ...
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

Latent Space Bayesian Parameter Topology Optimization of Permanent Magnet Synchronous Motors via a Variational Autoencoder

Abstract: This study introduces a novel approach that combines a variational autoencoder and Bayesian optimization to accelerate the simultaneous parameter and topology optimization of interior ...