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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 601–650 of 2050 papers

TitleStatusHype
A Unified Model Selection Technique for Spectral Clustering Based Motion Segmentation—0
Defining Expertise: Applications to Treatment Effect EstimationCode0
Unveiling the Potential of Robustness in Selecting Conditional Average Treatment Effect EstimatorsCode0
Z-AGI Labs at ClimateActivism 2024: Stance and Hate Event Detection on Social Media—0
Comparative Analysis of Data Preprocessing Methods, Feature Selection Techniques and Machine Learning Models for Improved Classification and Regression Performance on Imbalanced Genetic Data—0
Learning under Singularity: An Information Criterion improving WBIC and sBIC—0
Towards Versatile Graph Learning Approach: from the Perspective of Large Language Models—0
Modeling methodology for the accurate and prompt prediction of symptomatic events in chronic diseases—0
Confidence-aware Fine-tuning of Sequential Recommendation Systems via Conformal Prediction—0
Model Assessment and Selection under Temporal Distribution ShiftCode0
Online Foundation Model Selection in Robotics—0
Understanding Model Selection For Learning In Strategic Environments—0
Compressive Recovery of Signals Defined on Perturbed Graphs—0
Label-Efficient Model Selection for Text Generation—0
Local Projections Inference with High-Dimensional Covariates without Sparsity—0
Unsupervised Optimisation of GNNs for Node Clustering—0
Selective linear segmentation for detecting relevant parameter changes—0
Pretrained Generative Language Models as General Learning Frameworks for Sequence-Based Tasks—0
A Bandit Approach with Evolutionary Operators for Model Selection—0
Tuning In: Analysis of Audio Classifier Performance in Clinical Settings with Limited Data—0
A Bias-Variance Decomposition for Ensembles over Multiple Synthetic DatasetsCode0
Best Practices for Text Annotation with Large Language Models—0
Absolute convergence and error thresholds in non-active adaptive sampling—0
Surfing the modeling of PoS taggers in low-resource scenarios—0
tnGPS: Discovering Unknown Tensor Network Structure Search Algorithms via Large Language Models (LLMs)Code0
Data-driven model selection within the matrix completion method for causal panel data models—0
When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model LeaderboardsCode0
A Personalized Framework for Consumer and Producer Group Fairness Optimization in Recommender SystemsCode0
Dropout-Based Rashomon Set Exploration for Efficient Predictive Multiplicity Estimation—0
Dynamical System Identification, Model Selection and Model Uncertainty Quantification by Bayesian Inference—0
MT-HCCAR: Multi-Task Deep Learning with Hierarchical Classification and Attention-based Regression for Cloud Property RetrievalCode0
Green Runner: A tool for efficient deep learning component selection—0
Is K-fold cross validation the best model selection method for Machine Learning?—0
Fast Partition-Based Cross-Validation With Centering and Scaling for X^TX and X^TY—0
Towards Improved Variational Inference for Deep Bayesian Models—0
Budgeted Online Model Selection and Fine-Tuning via Federated Learning—0
DiffusionGPT: LLM-Driven Text-to-Image Generation System—0
Valid causal inference with unobserved confounding in high-dimensional settingsCode0
An Axiomatic Approach to Model-Agnostic Concept Explanations—0
Arrival Time Prediction for Autonomous Shuttle Services in the Real World: Evidence from Five Cities—0
Experiment Planning with Function Approximation—0
Music Genre Classification: A Comparative Analysis of CNN and XGBoost Approaches with Mel-frequency cepstral coefficients and Mel Spectrograms—0
Understanding Short-Term Implied Volatility Dynamics: A Model-Independent Approach Beyond Stochastic Volatility—0
Comprehensive Exploration of Synthetic Data Generation: A Survey—0
U-Trustworthy Models.Reliability, Competence, and Confidence in Decision-Making—0
Few-shot Adaptation of Multi-modal Foundation Models: A Survey—0
Explainable Adaptive Tree-based Model Selection for Time Series Forecasting—0
Automated Model Selection for Tabular DataCode0
Enhancing the Power of OOD Detection via Sample-Aware Model Selection—0
Downstream Task-Oriented Generative Model Selections on Synthetic Data Training for Fraud Detection Models—0
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