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Hyperparameter Optimization

Hyperparameter Optimization is the problem of choosing a set of optimal hyperparameters for a learning algorithm. Whether the algorithm is suitable for the data directly depends on hyperparameters, which directly influence overfitting or underfitting. Each model requires different assumptions, weights or training speeds for different types of data under the conditions of a given loss function.

Source: Data-driven model for fracturing design optimization: focus on building digital database and production forecast

Papers

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Showing 676–700 of 813 papers

TitleStatusHype
PHS: A Toolbox for Parallel Hyperparameter SearchCode0
HPO X ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape AnalysisCode0
Improving Hyperparameter Learning under Approximate Inference in Gaussian Process ModelsCode0
apsis - Framework for Automated Optimization of Machine Learning Hyper ParametersCode0
Hodge-Compositional Edge Gaussian ProcessesCode0
HEBO Pushing The Limits of Sample-Efficient Hyperparameter OptimisationCode0
Tabular Benchmarks for Joint Architecture and Hyperparameter OptimizationCode0
MARTHE: Scheduling the Learning Rate Via Online HypergradientsCode0
Bilevel Optimization under Unbounded Smoothness: A New Algorithm and Convergence AnalysisCode0
Integration of nested cross-validation, automated hyperparameter optimization, high-performance computing to reduce and quantify the variance of test performance estimation of deep learning modelsCode0
Intelligent Learning Rate Distribution to reduce Catastrophic Forgetting in TransformersCode0
Accelerating Neural Architecture Search using Performance PredictionCode0
Interactive Hyperparameter Optimization in Multi-Objective Problems via Preference LearningCode0
Warm Starting CMA-ES for Hyperparameter OptimizationCode0
Practical Bayesian Optimization of Machine Learning AlgorithmsCode0
Investigating the Impact of Hard Samples on Accuracy Reveals In-class Data ImbalanceCode0
An Automated Text Categorization Framework based on Hyperparameter OptimizationCode0
Bilevel Learning with Inexact Stochastic GradientsCode0
Is One Epoch All You Need For Multi-Fidelity Hyperparameter Optimization?Code0
Teaching Specific Scientific Knowledge into Large Language Models through Additional TrainingCode0
Iterative Deepening HyperbandCode0
Web Links Prediction And Category-Wise Recommendation Based On Browser HistoryCode0
Automated Image Captioning with CNNs and TransformersCode0
k-Mixup Regularization for Deep Learning via Optimal TransportCode0
Knowledge-augmented Pre-trained Language Models for Biomedical Relation ExtractionCode0
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