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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

Showing 751775 of 813 papers

TitleStatusHype
Optimizing for Generalization in Machine Learning with Cross-Validation GradientsCode0
Holarchic Structures for Decentralized Deep Learning - A Performance Analysis0
Rafiki: Machine Learning as an Analytics Service SystemCode0
Scalable Factorized Hierarchical Variational Autoencoder TrainingCode0
An LP-based hyperparameter optimization model for language modeling0
Best arm identification in multi-armed bandits with delayed feedback0
Natural Gradient Deep Q-learning0
Reviving and Improving Recurrent Back-PropagationCode0
Autostacker: A Compositional Evolutionary Learning System0
Practical Transfer Learning for Bayesian OptimizationCode0
Combination of Hyperband and Bayesian Optimization for Hyperparameter Optimization in Deep Learning0
Online Hyper-Parameter Optimization0
AMLA: an AutoML frAmework for Neural Network Design0
A Bridge Between Hyperparameter Optimization and Learning-to-learnCode0
Learning Surrogate Models of Document Image Quality Metrics for Automated Document Image Processing0
ATM: A distributed, collaborative, scalable system for automated machine learningCode0
Are GANs Created Equal? A Large-Scale StudyCode0
Transfer Learning to Learn with Multitask Neural Model Search0
Learning to Warm-Start Bayesian Hyperparameter Optimization0
SHADHO: Massively Scalable Hardware-Aware Distributed Hyperparameter Optimization0
Open Loop Hyperparameter Optimization and Determinantal Point Processes0
Hyperparameter Optimization: A Spectral ApproachCode0
Accelerating Neural Architecture Search using Performance PredictionCode0
An effective algorithm for hyperparameter optimization of neural networks0
DeepArchitect: Automatically Designing and Training Deep ArchitecturesCode0
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