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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 101–150 of 813 papers

TitleStatusHype
FLAML: A Fast and Lightweight AutoML LibraryCode1
Recursive Gaussian Process State Space ModelCode1
Meta-Surrogate Benchmarking for Hyperparameter OptimizationCode1
Generative Adversarial Neural OperatorsCode1
Self-Tuning Networks: Bilevel Optimization of Hyperparameters using Structured Best-Response FunctionsCode1
Nystrom Method for Accurate and Scalable Implicit DifferentiationCode1
GPT Takes the Bar ExamCode1
Exploring the Loss Landscape in Neural Architecture SearchCode1
Start Small, Think Big: On Hyperparameter Optimization for Large-Scale Knowledge Graph EmbeddingsCode1
Automated Hyperparameter Optimization Challenge at CIKM 2021 AnalyticCupCode1
LibKGE - A knowledge graph embedding library for reproducible researchCode1
Automated Machine Learning in InsuranceCode1
MANGO: A Python Library for Parallel Hyperparameter TuningCode1
LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for LassoCode1
In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter OptimizationCode1
High-Dimensional Bayesian Optimization via Additive Models with Overlapping GroupsCode1
HO-FMN: Hyperparameter Optimization for Fast Minimum-Norm AttacksCode1
The Value of Out-of-Distribution DataCode1
Using Large Language Models for Hyperparameter OptimizationCode1
AutoML: A Survey of the State-of-the-ArtCode1
Kronecker Decomposition for Knowledge Graph EmbeddingsCode1
HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPOCode1
A System for Massively Parallel Hyperparameter TuningCode1
AutoMMLab: Automatically Generating Deployable Models from Language Instructions for Computer Vision TasksCode1
HyperNOs: Automated and Parallel Library for Neural Operators ResearchCode1
Window Size Selection in Unsupervised Time Series Analytics: A Review and BenchmarkCode1
Implicit differentiation of Lasso-type models for hyperparameter optimizationCode1
Hyperparameter optimization in deep multi-target predictionCode1
Bilevel Fast Scene Adaptation for Low-Light Image EnhancementCode1
Hyperparameter Optimization via Sequential Uniform DesignsCode1
Improving Fast Minimum-Norm Attacks with Hyperparameter OptimizationCode1
Model Parameter Identification via a Hyperparameter Optimization Scheme for Autonomous Racing SystemsCode1
Implicit differentiation for fast hyperparameter selection in non-smooth convex learningCode1
Bag of Baselines for Multi-objective Joint Neural Architecture Search and Hyperparameter OptimizationCode1
Hyperparameter Importance Across DatasetsCode1
BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture SearchCode1
BOME! Bilevel Optimization Made Easy: A Simple First-Order ApproachCode1
BOHB: Robust and Efficient Hyperparameter Optimization at ScaleCode1
AutoProteinEngine: A Large Language Model Driven Agent Framework for Multimodal AutoML in Protein EngineeringCode1
LEMUR Neural Network Dataset: Towards Seamless AutoMLCode1
Enabling hyperparameter optimization in sequential autoencoders for spiking neural dataCode1
Bilevel Optimization with a Lower-level Contraction: Optimal Sample Complexity without Warm-startCode1
Improving Hyperparameter Optimization with Checkpointed Model WeightsCode1
Provably Efficient Online Hyperparameter Optimization with Population-Based BanditsCode1
PriorBand: Practical Hyperparameter Optimization in the Age of Deep LearningCode1
A Rigorous Machine Learning Analysis Pipeline for Biomedical Binary Classification: Application in Pancreatic Cancer Nested Case-control Studies with Implications for Bias AssessmentsCode1
Auto-nnU-Net: Towards Automated Medical Image SegmentationCode0
HyperController: A Hyperparameter Controller for Fast and Stable Training of Reinforcement Learning Neural NetworksCode0
HyperNOMAD: Hyperparameter optimization of deep neural networks using mesh adaptive direct searchCode0
AutoML for Multi-Class Anomaly Compensation of Sensor DriftCode0
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