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 21–30 of 813 papers

Title	Date	Tasks	Status	Hype	Score
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization	Sep 20, 2021	AutoMLBayesian Optimization	CodeCode Available	2	5
Visual Speech Recognition for Multiple Languages in the Wild	Feb 26, 2022	Hyperparameter OptimizationLipreading	CodeCode Available	2	5
An Empirical Study on Hyperparameter Optimization for Fine-Tuning Pre-trained Language Models	Jun 17, 2021	Hyperparameter Optimization	CodeCode Available	2	5
On Hyperparameter Optimization of Machine Learning Algorithms: Theory and Practice	Jul 30, 2020	AutoMLBIG-bench Machine Learning	CodeCode Available	2	5
One Configuration to Rule Them All? Towards Hyperparameter Transfer in Topic Models using Multi-Objective Bayesian Optimization	Feb 15, 2022	AllBayesian Optimization	CodeCode Available	2	5
Out-of-sample scoring and automatic selection of causal estimators	Dec 20, 2022	Causal InferenceHyperparameter Optimization	CodeCode Available	2	5
Hyperparameter Optimization for Randomized Algorithms: A Case Study on Random Features	Jun 30, 2024	GPRHyperparameter Optimization	CodeCode Available	2	5
A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning	Dec 12, 2010	Bayesian OptimizationHierarchical Reinforcement Learning	CodeCode Available	2	5
Frugal Optimization for Cost-related Hyperparameters	May 4, 2020	AutoMLBIG-bench Machine Learning	CodeCode Available	2	5
A Rigorous Machine Learning Analysis Pipeline for Biomedical Binary Classification: Application in Pancreatic Cancer Nested Case-control Studies with Implications for Bias Assessments	Aug 28, 2020	Binary Classificationfeature selection	CodeCode Available	1	5

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