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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 801–825 of 2050 papers

TitleStatusHype
Forecasting large collections of time series: feature-based methods—0
Forecasting Whole-Brain Neuronal Activity from Volumetric Video—0
Determine-Then-Ensemble: Necessity of Top-k Union for Large Language Model Ensembling—0
Forward and Backward Feature Selection for Query Performance Prediction—0
Forward utilities and Mean-field games under relative performance concerns—0
A new approach in model selection for ordinal target variables—0
Determination of Latent Dimensionality in International Trade Flow—0
Detection of Unobserved Common Causes based on NML Code in Discrete, Mixed, and Continuous Variables—0
Frame Fusion with Vehicle Motion Prediction for 3D Object Detection—0
A simple application of FIC to model selection—0
From Human Annotation to LLMs: SILICON Annotation Workflow for Management Research—0
From Structured to Unstructured:A Comparative Analysis of Computer Vision and Graph Models in solving Mesh-based PDEs—0
Functional additive models on manifolds of planar shapes and forms—0
Fundamental limits to learning closed-form mathematical models from data—0
A Bayesian Model for Bivariate Causal Inference—0
Accessible, At-Home Detection of Parkinson's Disease via Multi-task Video Analysis—0
Fuzzy Fibers: Uncertainty in dMRI Tractography—0
Classification with Scattering Operators—0
Fast and Accurate Graph Learning for Huge Data via Minipatch Ensembles—0
Gaussian Mixture Clustering Using Relative Tests of Fit—0
Gaussian Process-based Spatial Reconstruction of Electromagnetic fields—0
Gaussian process modeling in approximate Bayesian computation to estimate horizontal gene transfer in bacteria—0
AssistedDS: Benchmarking How External Domain Knowledge Assists LLMs in Automated Data Science—0
Action-State Dependent Dynamic Model Selection—0
Detection of intensity bursts using Hawkes processes: an application to high frequency financial data—0
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