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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 1226–1250 of 2050 papers

TitleStatusHype
Generative Model Selection Using a Scalable and Size-Independent Complex Network Classifier—0
Geometric and Topological Inference for Deep Representations of Complex Networks—0
Global Adaptive Generative Adjustment—0
Global sensitivity analysis informed model reduction and selection applied to a Valsalva maneuver model—0
Going off the Grid: Iterative Model Selection for Biclustered Matrix Completion—0
GPT in Data Science: A Practical Exploration of Model Selection—0
Gradient-based Hyperparameter Optimization without Validation Data for Learning fom Limited Labels—0
Gradient Boosting for Spatial Regression Models with Autoregressive Disturbances—0
Graph-based regularization for regression problems with alignment and highly-correlated designs—0
Graph Coding for Model Selection and Anomaly Detection in Gaussian Graphical Models—0
Graphical LASSO Based Model Selection for Time Series—0
Graph Similarity Description: How Are These Graphs Similar?—0
Graph vs. Sequence: An Empirical Study on Knowledge Forms for Knowledge-Grounded Dialogue—0
GRASMOS: Graph Signage Model Selection for Gene Regulatory Networks—0
Greedy equivalence search for nonparametric graphical models—0
Greedy metrics in orthogonal greedy learning—0
Greedy Model Averaging—0
Green AI in Action: Strategic Model Selection for Ensembles in Production—0
Green Runner: A tool for efficient deep learning component selection—0
Green Runner: A tool for efficient model selection from model repositories—0
GRIDS: Grouped Multiple-Degradation Restoration with Image Degradation Similarity—0
Group-Sparse Model Selection: Hardness and Relaxations—0
Guided Recommendation for Model Fine-Tuning—0
Guided Sampling-based Evolutionary Deep Neural Network for Intelligent Fault Diagnosis—0
GujiBERT and GujiGPT: Construction of Intelligent Information Processing Foundation Language Models for Ancient Texts—0
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