Results 181 to 190 of about 47,583 (209)

SLURM-Managed HyperParameter Optimization.

Hyperparameter optimization (HPO) is essential for achieving state-of-the-art performance in machine learning, yet it is computationally demanding, particularly on shared or resource-constrained clusters. We present a system that integrates the Asynchronous Successive Halving Algorithm (ASHA) with SEML, the SLURM Experiment Management Library - an ...
Chattopadhyay, Anusha, Borras, Hendrik, Klein, Bernhard, Fröning, Holger   +3 more
openaire   +2 more sources

LiDAR-in-the-Loop Hyperparameter Optimization

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023
Félix Goudreault, Dominik Scheuble, Mario Bijelic, Nicolas Robidoux, Felix Heide   +4 more
openaire   +1 more source

Surrogate-Assisted Hybrid-Model Estimation of Distribution Algorithm for Mixed-Variable Hyperparameters Optimization in Convolutional Neural Networks

IEEE Transactions on Neural Networks and Learning Systems, 2023
Jian-Yu Li, Zhi-Hui Zhan, Sam Kwong
exaly  

On the use of acquisition function‐based Bayesian optimization method to efficiently tune SVM hyperparameters for structural damage detection

Structural Control and Health Monitoring, 2021
Anand Kumar Agrawal, Goutam Chakraborty
exaly  

Optimization and application of the distribution of relaxation times based on characteristic frequency resolution and hyperparameters

Journal of Power Sources, 2022
Dong Zhu, Tiancai Ma, Yanbo Yang
exaly  

On Hyperparameter Optimization in Learning Systems.

2019
We study two procedures (reverse-mode and forward-mode) for computing the gradient of the validation error with respect to the hyperparameters of any iterative learning algorithm. These procedures mirror two ways of computing gradients for recurrent neural networks and have different trade-offs in terms of running time and space requirements.
Franceschi L., Donini M., Frasconi P., Pontil M.   +3 more
openaire   +2 more sources

Hyperparameter Optimization

2022
openaire   +1 more source

Scalable Meta-Bayesian Based Hyperparameters Optimization for Machine Learning

Communications in Computer and Information Science, 2023
Adeel Ahmad, Mourad Bouneffa, Mohamed Hamlich   +2 more
exaly  

How to tune the RBF SVM hyperparameters? An empirical evaluation of 18 search algorithms

Artificial Intelligence Review, 2021
Jacques Wainer, Pablo Fonseca, Wainer Jacques   +2 more
exaly  

Computer Optimization of ANN Hyperparameters for Retrospective Information Processing

Lecture Notes in Networks and Systems, 2022
Elena V Melikhova, Aleksey F Rogachev
exaly