Results 81 to 90 of about 47,583 (209)

Bayesian Optimization of Hyperparameters in Machine Learning

, 2021
Cilj naše diplomske naloge je bil analizirati Bayesovsko optimizacijo na problemu optimizacije hiperparametrov. Podlaga za analizo sta pogosto uporabljani orodji za optimizacijo hiperparametrov: naključno iskanje in iskanje v mreži.
OCEPEK, DAVID
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Hyperparameter Optimization

The Journal of The Institute of Image Information and Television Engineers, 2023
Marc Becker, Lennart Schneider, Sebastian Fischer   +2 more
openaire   +2 more sources

Bayesian Optimization of Hyperparameters Using Gaussian Processes

, 2019
The goal of this thesis was to implement a practical tool for optimizing hy- perparameters of neural networks using Bayesian optimization. We show the theoretical foundations of Bayesian optimization, including the necessary math- ematical background for
Arnold, Jakub
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Hyperparameters of machine learning model obtained by Bayesian optimization.

Hyperparameters of machine learning model obtained by Bayesian optimization.
Xue Liu (420033), Chen Zhu (445894), Dong Chen (448284)   +2 more
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Robust optimization of SVM hyperparameters in the classification of bioactive compounds

, 2015
Background: Support Vector Machine has become one of the most popular machine learning tools used in virtual screening campaigns aimed at finding new drug candidates. Although it can be extremely effective in finding new potentially active compounds, its
Podlewska, Sabina, Czarnecki, Wojciech, Wojciech M Czarnecki, Bojarski, Andrzej J., Sabina Podlewska, Andrzej J Bojarski   +5 more
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Optimizing Hyperparameters in Deep Learning Models Using Bayesian Optimization [PDF]

Hyperparameter optimization is a crucial aspect of deep learning, as the choice of hyperparameters significantly influences model performance.
Kian Hemant, Madan
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A New Hyperparameter Tuning Framework for Regression Tasks in Deep Neural Network: Combined-Sampling Algorithm to Search the Optimized Hyperparameters

Mathematics
This paper introduces a novel hyperparameter optimization framework for regression tasks called the Combined-Sampling Algorithm to Search the Optimized Hyperparameters (CASOH).
Nguyen Huu Tiep, Hae-Yong Jeong, Kyung-Doo Kim, Nguyen Xuan Mung, Nhu-Ngoc Dao, Hoai-Nam Tran, Van-Khanh Hoang, Nguyen Ngoc Anh, Mai The Vu   +8 more
doaj   +1 more source

Feature-Based Population Initialization for Evolutionary Optimization of Machine Learning Models in Short-Term Solar Power Forecasting

Computation
Nowadays, solar energy is becoming one of the most popular sources of renewable energy worldwide. Traditional fossil fuels cause pollution and climate change, while solar power offers a clean and sustainable alternative.
Aleksei Vakhnin, Harri Niska, Anders V. Lindfors, Mikko Kolehmainen   +3 more
doaj   +1 more source

A Combinatorial Approach to Hyperparameter Optimization

Proceedings of the IEEE/ACM 3rd International Conference on AI Engineering - Software Engineering for AI
Published ...
Krishna Khadka, Jaganmohan Chandrasekaran, Yu Lei 0001, Raghu N. Kacker, D. Richard Kuhn   +4 more
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Efficient Hyperparameter Tuning with Dynamic Accuracy Derivative-Free Optimization

, 2022
Many machine learning solutions are framed as optimization problems which rely on good hyperparameters. Algorithms for tuning these hyperparameters usually assume access to exact solutions to the underlying learning problem, which is typically not ...
Roberts, Lindon, Ehrhardt, Matthias
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