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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
PyTorch Hyperparameter Tuning - A Tutorial for spotPythonCode1
RBFOpt: an open-source library for black-box optimization with costly function evaluationsCode1
An Asymptotically Optimal Multi-Armed Bandit Algorithm and Hyperparameter OptimizationCode1
Heuristic Hyperparameter Optimization for Convolutional Neural Networks using Genetic AlgorithmCode1
MFES-HB: Efficient Hyperband with Multi-Fidelity Quality MeasurementsCode1
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
Stabilizing Bi-Level Hyperparameter Optimization using Moreau-Yosida RegularizationCode1
Automated Hyperparameter Optimization Challenge at CIKM 2021 AnalyticCupCode1
Provably Efficient Online Hyperparameter Optimization with Population-Based BanditsCode1
A System for Massively Parallel Hyperparameter TuningCode1
Exploring the Loss Landscape in Neural Architecture SearchCode1
LEMUR Neural Network Dataset: Towards Seamless AutoMLCode1
A Data-Centric Perspective on Evaluating Machine Learning Models for Tabular DataCode1
HomOpt: A Homotopy-Based Hyperparameter Optimization MethodCode1
HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPOCode1
Model Parameter Identification via a Hyperparameter Optimization Scheme for Autonomous Racing SystemsCode1
LibKGE - A knowledge graph embedding library for reproducible researchCode1
AutoML: A Survey of the State-of-the-ArtCode1
Anisotropic 3D Multi-Stream CNN for Accurate Prostate Segmentation from Multi-Planar MRICode1
Using Large Language Models for Hyperparameter OptimizationCode1
Meta-Learning in Neural Networks: A SurveyCode1
AutoMMLab: Automatically Generating Deployable Models from Language Instructions for Computer Vision TasksCode1
Where Did the Gap Go? Reassessing the Long-Range Graph BenchmarkCode1
Window Size Selection in Unsupervised Time Series Analytics: A Review and BenchmarkCode1
In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter OptimizationCode1
Implicit differentiation of Lasso-type models for hyperparameter optimizationCode1
Bilevel Optimization with a Lower-level Contraction: Optimal Sample Complexity without Warm-startCode1
Improving Fast Minimum-Norm Attacks with Hyperparameter OptimizationCode1
Kronecker Decomposition for Knowledge Graph EmbeddingsCode1
Hyperparameter optimization in deep multi-target predictionCode1
Improving Hyperparameter Optimization with Checkpointed Model WeightsCode1
Bag of Baselines for Multi-objective Joint Neural Architecture Search and Hyperparameter OptimizationCode1
BOHB: Robust and Efficient Hyperparameter Optimization at ScaleCode1
BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture SearchCode1
Hyperparameter Optimization via Sequential Uniform DesignsCode1
BOME! Bilevel Optimization Made Easy: A Simple First-Order ApproachCode1
AutoProteinEngine: A Large Language Model Driven Agent Framework for Multimodal AutoML in Protein EngineeringCode1
Enabling hyperparameter optimization in sequential autoencoders for spiking neural dataCode1
Bilevel Fast Scene Adaptation for Low-Light Image EnhancementCode1
MANGO: A Python Library for Parallel Hyperparameter TuningCode1
Implicit differentiation for fast hyperparameter selection in non-smooth convex learningCode1
LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for LassoCode1
Meta-Surrogate Benchmarking for Hyperparameter OptimizationCode1
Promoting Fairness through Hyperparameter OptimizationCode1
Auto-nnU-Net: Towards Automated Medical Image SegmentationCode0
Hyperopt: A Python Library for Optimizing the Hyperparameters of Machine Learning AlgorithmsCode0
Hyperopt-Sklearn: Automatic Hyperparameter Configuration for Scikit-LearnCode0
Hyperparameter-free and Explainable Whole Graph EmbeddingCode0
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