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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 551–600 of 813 papers

TitleStatusHype
Evaluating Transferability of BERT Models on Uralic LanguagesCode0
A comparative study of six model complexity metrics to search for parsimonious models with GAparsimony R Package—0
RF-LighGBM: A probabilistic ensemble way to predict customer repurchase behaviour in community e-commerce—0
To tune or not to tune? An Approach for Recommending Important Hyperparameters—0
CrossedWires: A Dataset of Syntactically Equivalent but Semantically Disparate Deep Learning ModelsCode0
MOFit: A Framework to reduce Obesity using Machine learning and IoT—0
Is Differentiable Architecture Search truly a One-Shot Method?—0
Hyperparameter-free and Explainable Whole Graph EmbeddingCode0
Transformers for Low-Resource Languages: Is Féidir Linn!—0
Bilevel Optimization for Machine Learning: Algorithm Design and Convergence Analysis—0
Enhanced Bilevel Optimization via Bregman Distance—0
Experimental Investigation and Evaluation of Model-based Hyperparameter Optimization—0
Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges—0
Automated Graph Learning via Population Based Self-Tuning GCN—0
Preconditioning for Scalable Gaussian Process Hyperparameter Optimization—0
Tuning Mixed Input Hyperparameters on the Fly for Efficient Population Based AutoRL—0
Using deep learning to detect patients at risk for prostate cancer despite benign biopsies—0
Batch Multi-Fidelity Bayesian Optimization with Deep Auto-Regressive Networks—0
A Nonmyopic Approach to Cost-Constrained Bayesian OptimizationCode0
Meta-Learning for Symbolic Hyperparameter DefaultsCode0
Stability and Generalization of Bilevel Programming in Hyperparameter OptimizationCode0
Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing—0
k-Mixup Regularization for Deep Learning via Optimal TransportCode0
SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit modelsCode0
BERT Goes Brrr: A Venture Towards the Lesser Error in Classifying Medical Self-Reporters on Twitter—0
The Imaginative Generative Adversarial Network: Automatic Data Augmentation for Dynamic Skeleton-Based Hand Gesture and Human Action Recognition—0
Techniques Toward Optimizing Viewability in RTB Ad Campaigns Using Reinforcement Learning—0
Leveraging Theoretical Tradeoffs in Hyperparameter Selection for Improved Empirical Performance—0
Towards Explaining Hyperparameter Optimization via Partial Dependence Plots—0
Efficient Hyperparameter Optimization for Physics-based Character Animation—0
Automatic Termination for Hyperparameter OptimizationCode0
Which Hyperparameters to Optimise? An Investigation of Evolutionary Hyperparameter Optimisation in Graph Neural Network For Molecular Property Prediction—0
Use of static surrogates in hyperparameter optimization—0
Convolution Neural Network Hyperparameter Optimization Using Simplified Swarm Optimization—0
Genetic Algorithm based hyper-parameters optimization for transfer Convolutional Neural Network—0
Mixed Variable Bayesian Optimization with Frequency Modulated Kernels—0
A Novel Non-Invasive Estimation of Respiration Rate from Photoplethysmograph Signal Using Machine Learning Model—0
Optimizing Large-Scale Hyperparameters via Automated Learning AlgorithmCode0
A Near-Optimal Algorithm for Stochastic Bilevel Optimization via Double-Momentum—0
A Systematic Comparison Study on Hyperparameter Optimisation of Graph Neural Networks for Molecular Property Prediction—0
Hyperparameter Optimization with Differentiable Metafeatures—0
Hyperparameter Optimization Is Deceiving Us, and How to Stop ItCode0
One Size Does Not Fit All: Finding the Optimal Subword Sizes for FastText Models across Languages—0
Incremental Search Space Construction for Machine Learning Pipeline Synthesis—0
A Novel Genetic Algorithm with Hierarchical Evaluation Strategy for Hyperparameter Optimisation of Graph Neural Networks—0
Optimizing Hyperparameters in CNNs using Bilevel Programming in Time Series Data—0
Few-Shot Bayesian Optimization with Deep Kernel Surrogates—0
Cost-Efficient Online Hyperparameter Optimization—0
Hyperboost: Hyperparameter Optimization by Gradient Boosting surrogate models—0
Regularization Cocktails—0
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