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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 951–1000 of 2050 papers

TitleStatusHype
Inertial Regularization and Selection (IRS): Sequential Regression in High-Dimension and Sparsity—0
Fast Linear Model Trees by PILOT—0
InfantCryNet: A Data-driven Framework for Intelligent Analysis of Infant Cries—0
SMRS: advocating a unified reporting standard for surrogate models in the artificial intelligence era—0
Inferring bias and uncertainty in camera calibration—0
Fast leave-one-cluster-out cross-validation using clustered Network Information Criterion (NICc)—0
A Regret-Variance Trade-Off in Online Learning—0
Fast approximations of the Jeffreys divergence between univariate Gaussian mixture models via exponential polynomial densities—0
Inferring Network Structure From Data—0
Carbon Intensity-Aware Adaptive Inference of DNNs—0
Fast Approximate Bayesian Computation for Estimating Parameters in Differential Equations—0
Fast and Robust Part-of-Speech Tagging Using Dynamic Model Selection—0
Carbon Footprint of Selecting and Training Deep Learning Models for Medical Image Analysis—0
Area under the ROC Curve has the Most Consistent Evaluation for Binary Classification—0
Information criteria for non-normalized models—0
Information Theoretic Guarantees for Empirical Risk Minimization with Applications to Model Selection and Large-Scale Optimization—0
Informative Bayesian model selection for RR Lyrae star classifiers—0
Double Descent Risk and Volume Saturation Effects: A Geometric Perspective—0
A convex pseudo-likelihood framework for high dimensional partial correlation estimation with convergence guarantees—0
A Bayesian Approach to Network Modularity—0
On the Problem of Text-To-Speech Model Selection for Synthetic Data Generation in Automatic Speech Recognition—0
Inter-domain Gaussian Processes for Sparse Inference using Inducing Features—0
Interpretability in Linear Brain Decoding—0
Quantitative Overfitting Management for Human-in-the-loop ML Application Development with ease.ml/meter—0
Interpretable Machine Learning for Discovery: Statistical Challenges \& Opportunities—0
Interpretable Machine Learning for Self-Service High-Risk Decision-Making—0
Fast and fully-automated histograms for large-scale data sets—0
Capturing and incorporating expert knowledge into machine learning models for quality prediction in manufacturing—0
Fair Community Detection and Structure Learning in Heterogeneous Graphical Models—0
Capitalizing on a Crisis: A Computational Analysis of all Five Million British Firms During the Covid-19 Pandemic—0
MF-CLIP: Leveraging CLIP as Surrogate Models for No-box Adversarial Attacks—0
fairml: A Statistician's Take on Fair Machine Learning Modelling—0
Can We Use Gradient Norm as a Measure of Generalization Error for Model Selection in Practice?—0
Factors in Fashion: Factor Analysis towards the Mode—0
Model Selection for Inverse Reinforcement Learning via Structural Risk Minimization—0
Factorized Asymptotic Bayesian Inference for Latent Feature Models—0
Factorized Asymptotic Bayesian Inference for Factorial Hidden Markov Models—0
Can Pre-training Indicators Reliably Predict Fine-tuning Outcomes of LLMs?—0
Is F_1 Score Suboptimal for Cybersecurity Models? Introducing C_score, a Cost-Aware Alternative for Model Assessment—0
Ising Model Selection Using _1-Regularized Linear Regression: A Statistical Mechanics Analysis—0
Is it worth it? Budget-related evaluation metrics for model selection—0
Is K-fold cross validation the best model selection method for Machine Learning?—0
Factor-Augmented Regularized Model for Hazard Regression—0
Face Recognition using Optimal Representation Ensemble—0
IW-GAE: Importance Weighted Group Accuracy Estimation for Improved Calibration and Model Selection in Unsupervised Domain Adaptation—0
Joint Continuous and Discrete Model Selection via Submodularity—0
Face Recognition Using Deep Multi-Pose Representations—0
Can Large Language Models Capture Public Opinion about Global Warming? An Empirical Assessment of Algorithmic Fidelity and Bias—0
Agentic AI Systems Applied to tasks in Financial Services: Modeling and model risk management crews—0
FA3L at SemEval-2017 Task 3: A ThRee Embeddings Recurrent Neural Network for Question Answering—0
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