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Model Selection

Given a set of candidate models, the goal of Model Selection is to select the model that best approximates the observed data and captures its underlying regularities. Model Selection criteria are defined such that they strike a balance between the goodness of fit, and the generalizability or complexity of the models.

Source: Kernel-based Information Criterion

Papers

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Showing 651–700 of 2050 papers

TitleStatusHype
Bayesian model selection consistency and oracle inequality with intractable marginal likelihood—0
Efficient Sequential Decision Making with Large Language Models—0
Efficient speech detection in environmental audio using acoustic recognition and knowledge distillation—0
EL-MLFFs: Ensemble Learning of Machine Leaning Force Fields—0
Dimensionality Detection and Integration of Multiple Data Sources via the GP-LVM—0
EM Algorithms for Weighted-Data Clustering with Application to Audio-Visual Scene Analysis—0
Empirical analysis in limit order book modeling for Nikkei 225 Stocks with Cox-type intensities—0
Dimensionality Dependent PAC-Bayes Margin Bound—0
Empirical Comparison between Cross-Validation and Mutation-Validation in Model Selection—0
Bayesian Model Selection Approach to Boundary Detection with Non-Local Priors—0
Empirical Quantitative Analysis of COVID-19 Forecasting Models—0
Empowering Agricultural Insights: RiceLeafBD - A Novel Dataset and Optimal Model Selection for Rice Leaf Disease Diagnosis through Transfer Learning Technique—0
An HMM Approach with Inherent Model Selection for Sign Language and Gesture Recognition—0
Encoding-dependent generalization bounds for parametrized quantum circuits—0
End-to-End Edge AI Service Provisioning Framework in 6G ORAN—0
An Optimal Likelihood Free Method for Biological Model Selection—0
Energy-Aware Dynamic Neural Inference—0
Energy-Efficient Respiratory Anomaly Detection in Premature Newborn Infants—0
Efficient Distributed DNNs in the Mobile-edge-cloud Continuum—0
Enhancing Certifiable Robustness via a Deep Model Ensemble—0
Enhancing Offline Model-Based RL via Active Model Selection: A Bayesian Optimization Perspective—0
Enhancing the Power of OOD Detection via Sample-Aware Model Selection—0
Ensemble Method for Estimating Individualized Treatment Effects—0
Digital Twin-Assisted Knowledge Distillation Framework for Heterogeneous Federated Learning—0
Ensemble Reinforcement Learning: A Survey—0
DiffusionGPT: LLM-Driven Text-to-Image Generation System—0
Entropy-based Characterization of Modeling Constraints—0
Epidemic Dynamics via Wavelet Theory and Machine Learning, with Applications to Covid-19—0
Bayesian leave-one-out cross-validation for large data—0
Episodic memory for continual model learning—0
Selective machine learning of doubly robust functionals—0
Federated Learning with Correlated Data: Taming the Tail for Age-Optimal Industrial IoT—0
ER2Score: LLM-based Explainable and Customizable Metric for Assessing Radiology Reports with Reward-Control Loss—0
Error Reduction from Stacked Regressions—0
Bayesian Learning with Wasserstein Barycenters—0
DiffGAN: A Test Generation Approach for Differential Testing of Deep Neural Networks—0
Adaptive Sequential Machine Learning—0
Estimating Optimal Policy Value in General Linear Contextual Bandits—0
Estimating Real Log Canonical Thresholds—0
Estimating Stable Fixed Points and Langevin Potentials for Financial Dynamics—0
Achieving Fairness with a Simple Ridge Penalty—0
Estimating the Number of Components in Panel Data Finite Mixture Regression Models with an Application to Production Function Heterogeneity—0
Estimation of Heterogeneous Treatment Effects Using a Conditional Moment Based Approach—0
Estimation of Local Average Treatment Effect by Data Combination—0
Estimation vs Metrics: is QE Useful for MT Model Selection?—0
Explainable Adaptive Tree-based Model Selection for Time Series Forecasting—0
Differentially Private Learning with Margin Guarantees—0
How have German University Tuition Fees Affected Enrollment Rates: Robust Model Selection and Design-based Inference in High-Dimensions—0
Evaluating Gender Bias in Large Language Models—0
Differentially Private Generalized Linear Models Revisited—0
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