Results 241 to 250 of about 127,719 (261)

L-SHADE optimized learning framework for sEMG hand gesture recognition. [PDF]

Sci Rep
Gehlot N, Vijayvargiya A, Jena A, Kumar R, Hans S, Harjule P.   +5 more
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An attention based optimized network for the classification of skin lesions. [PDF]

Sci Rep
Priyadarsini RN, Tyagi B, Priyadharsini M.   +2 more
europepmc   +1 more source

Machine Learning Prediction of Road Performance of Cold Recycled Mix Asphalt with Genetic Algorithm Hyperparameter Optimization. [PDF]

Materials (Basel)
Wu Z, Li S, Wang D, Qiu M, Fang C, Yang J, Tang H.   +6 more
europepmc   +1 more source

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Reproducible Hyperparameter Optimization

Journal of Computational and Graphical Statistics, 2021
A key issue in machine learning research is the lack of reproducibility. We illustrate what role hyperparameter search plays in this problem and how regular hyperparameter search methods can lead t...
Lars Hertel, Pierre Baldi, Daniel L. Gillen   +2 more
openaire   +1 more source

Hyperparameter Optimization Machines

2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA), 2016
Algorithm selection and hyperparameter tuning are omnipresent problems for researchers and practitioners. Hence, it is not surprising that the efforts in automatizing this process using various meta-learning approaches have been increased. Sequential model-based optimization (SMBO) is ne of the most popular frameworks for finding optimal hyperparameter
Martin Wistuba, Nicolas Schilling, Lars Schmidt-Thieme   +2 more
openaire   +1 more source

Learning hyperparameter optimization initializations

2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA), 2015
Hyperparameter optimization is often done manually or by using a grid search. However, recent research has shown that automatic optimization techniques are able to accelerate this optimization process and find hyperparameter configurations that lead to better models.
Martin Wistuba, Nicolas Schilling, Lars Schmidt-Thieme   +2 more
openaire   +1 more source

Model-based hyperparameter optimization

2023
L’objectif principal de ce travail est de proposer une méthodologie de découverte des hyperparamètres. Les hyperparamètres aident les systèmes à converger lorsqu’ils sont bien réglés et fabriqués à la main. Cependant, à cette fin, des hyperparamètres mal choisis laissent les praticiens dans l’incertitude, entre soucis de mise en oeuvre ou mauvais choix
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Results for "Optimizing hyperparameters"

2020
Output from optimizing hyperparmeters, find scripts on https://github.com/asreview/paper-optimizing ...
van de Schoot, Rens, de Bruin, Jonathan, Ferdinands, Gerbrich   +2 more
openaire   +1 more source