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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 101–125 of 813 papers

TitleStatusHype
Gradient-based Hyperparameter Optimization Over Long HorizonsCode1
Nystrom Method for Accurate and Scalable Implicit DifferentiationCode1
An Asymptotically Optimal Multi-Armed Bandit Algorithm and Hyperparameter OptimizationCode1
BenchML: an extensible pipelining framework for benchmarking representations of materials and molecules at scaleCode1
Elliot: a Comprehensive and Rigorous Framework for Reproducible Recommender Systems EvaluationCode1
Online hyperparameter optimization by real-time recurrent learningCode1
EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter OptimizationCode1
On the Iteration Complexity of Hypergradient ComputationCode1
Optimal Hyperparameters for Deep LSTM-Networks for Sequence Labeling TasksCode1
Automated Hyperparameter Optimization Challenge at CIKM 2021 AnalyticCupCode1
Generative Adversarial Neural OperatorsCode1
Automated Machine Learning in InsuranceCode1
Supervising the Multi-Fidelity Race of Hyperparameter ConfigurationsCode1
Delta-STN: Efficient Bilevel Optimization for Neural Networks using Structured Response JacobiansCode1
DEHB: Evolutionary Hyperband for Scalable, Robust and Efficient Hyperparameter OptimizationCode1
PolyPose: Localizing Deformable Anatomy in 3D from Sparse 2D X-ray Images using Polyrigid TransformsCode1
Bilevel Fast Scene Adaptation for Low-Light Image EnhancementCode1
PriorBand: Practical Hyperparameter Optimization in the Age of Deep LearningCode1
PyHopper -- Hyperparameter optimizationCode1
AutoML: A Survey of the State-of-the-ArtCode1
Anisotropic 3D Multi-Stream CNN for Accurate Prostate Segmentation from Multi-Planar MRICode1
RBFOpt: an open-source library for black-box optimization with costly function evaluationsCode1
Does Long-Term Series Forecasting Need Complex Attention and Extra Long Inputs?Code1
AutoMMLab: Automatically Generating Deployable Models from Language Instructions for Computer Vision TasksCode1
Efficient Hyperparameter Optimization for Differentially Private Deep LearningCode1
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