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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 551–600 of 2050 papers

TitleStatusHype
Cost-efficient Knowledge-based Question Answering with Large Language Models—0
Comparative Study of Machine Learning Algorithms in Detecting Cardiovascular Diseases—0
IncomeSCM: From tabular data set to time-series simulator and causal estimation benchmarkCode0
Cross-Validated Off-Policy EvaluationCode0
AnyLoss: Transforming Classification Metrics into Loss FunctionsCode0
Symmetric Linear Bandits with Hidden SymmetryCode0
Green AI in Action: Strategic Model Selection for Ensembles in Production—0
Simultaneous Identification of Sparse Structures and Communities in Heterogeneous Graphical Models—0
Comparative Analysis of Predicting Subsequent Steps in Hénon Map—0
Robust Model Aggregation for Heterogeneous Federated Learning: Analysis and Optimizations—0
Bridging the Bosphorus: Advancing Turkish Large Language Models through Strategies for Low-Resource Language Adaptation and Benchmarking—0
Don't Waste Your Time: Early Stopping Cross-ValidationCode0
On Quantum Ambiguity and Potential Exponential Computational Speed-Ups to Solving Dynamic Asset Pricing Models—0
Misclassification bounds for PAC-Bayesian sparse deep learning—0
KITE: A Kernel-based Improved Transferability Estimation Method—0
MRScore: Evaluating Radiology Report Generation with LLM-based Reward System—0
Automated Model Selection for Generalized Linear Models—0
Estimating the Number of Components in Finite Mixture Models via Variational Approximation—0
mlr3summary: Concise and interpretable summaries for machine learning modelsCode0
On uncertainty-penalized Bayesian information criterion—0
Generalizing Machine Learning Evaluation through the Integration of Shannon Entropy and Rough Set Theory—0
A Sentiment Analysis of Medical Text Based on Deep Learning—0
On the Necessity of Collaboration for Online Model Selection with Decentralized Data—0
A Realistic Protocol for Evaluation of Weakly Supervised Object LocalizationCode0
Semantic Approach to Quantifying the Consistency of Diffusion Model Image GenerationCode0
Measuring Domain Shifts using Deep Learning Remote Photoplethysmography Model Similarity—0
Dimension-free Relaxation Times of Informed MCMC Samplers on Discrete Spaces—0
Model Selection with Model Zoo via Graph LearningCode0
Predictive Analytics of Varieties of PotatoesCode0
SpiKernel: A Kernel Size Exploration Methodology for Improving Accuracy of the Embedded Spiking Neural Network Systems—0
GLEMOS: Benchmark for Instantaneous Graph Learning Model SelectionCode0
Learning the mechanisms of network growthCode0
Beyond One-Size-Fits-All: Multi-Domain, Multi-Task Framework for Embedding Model Selection—0
Bayesian Nonparametrics: An Alternative to Deep Learning—0
Individual Text Corpora Predict Openness, Interests, Knowledge and Level of Education—0
EL-MLFFs: Ensemble Learning of Machine Leaning Force Fields—0
Carbon Intensity-Aware Adaptive Inference of DNNs—0
Conformal online model aggregationCode0
An Experimental Study on the Rashomon Effect of Balancing Methods in Imbalanced ClassificationCode0
Bridge the Modality and Capability Gaps in Vision-Language Model Selection—0
DiTMoS: Delving into Diverse Tiny-Model Selection on MicrocontrollersCode0
On the Laplace Approximation as Model Selection Criterion for Gaussian Processes—0
Evaluating Large Language Models as Generative User Simulators for Conversational RecommendationCode0
Pre-Trained Model Recommendation for Downstream Fine-tuning—0
Detection of Unobserved Common Causes based on NML Code in Discrete, Mixed, and Continuous Variables—0
Which LLM to Play? Convergence-Aware Online Model Selection with Time-Increasing Bandits—0
Regularized DeepIV with Model Selection—0
A data-centric approach to class-specific bias in image data augmentation—0
Dendrogram of mixing measures: Hierarchical clustering and model selection for finite mixture models—0
A Unified Model Selection Technique for Spectral Clustering Based Motion Segmentation—0
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