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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 1726–1750 of 2050 papers

TitleStatusHype
Compressive Nonparametric Graphical Model Selection For Time Series—0
Compressive Recovery of Signals Defined on Perturbed Graphs—0
Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference—0
Confidence-aware Fine-tuning of Sequential Recommendation Systems via Conformal Prediction—0
Confidence-based Ensembles of End-to-End Speech Recognition Models—0
Confidence-Based Model Selection: When to Take Shortcuts for Subpopulation Shifts—0
Conformal Prediction with Upper and Lower Bound Models—0
ConfusionFlow: A model-agnostic visualization for temporal analysis of classifier confusion—0
Conjugate Mixture Models for Clustering Multimodal Data—0
Consensual Aggregation on Random Projected High-dimensional Features for Regression—0
Consistencies and inconsistencies between model selection and link prediction in networks—0
Consistent model selection in the spiked Wigner model via AIC-type criteria—0
Consistent Nonparametric Different-Feature Selection via the Sparsest k-Subgraph Problem—0
Consistent Relative Confidence and Label-Free Model Selection for Convolutional Neural Networks—0
Contextual-Bandit Anomaly Detection for IoT Data in Distributed Hierarchical Edge Computing—0
Continual Learning Without Knowing Task Identities: Rethinking Occam's Razor—0
Continuous Bayesian Model Selection for Multivariate Causal Discovery—0
Sensitivity to control signals in triphasic rhythmic neural systems: a comparative mechanistic analysis via infinitesimal local timing response curves—0
Convergence Properties of Kronecker Graphical Lasso Algorithms—0
Convex Techniques for Model Selection—0
Boosting with copula-based components—0
Corpus-Based Paraphrase Detection Experiments and Review—0
Correcting Model Bias with Sparse Implicit Processes—0
Cost-Effective Online Contextual Model Selection—0
Cost-efficient Knowledge-based Question Answering with Large Language Models—0
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