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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 251–300 of 2050 papers

TitleStatusHype
An adaptive simulated annealing EM algorithm for inference on non-homogeneous hidden Markov modelsCode0
Impact of ImageNet Model Selection on Domain AdaptationCode0
Adaptive Concentration of Regression Trees, with Application to Random ForestsCode0
Improved Group Robustness via Classifier Retraining on Independent SplitsCode0
All models are wrong, some are useful: Model Selection with Limited LabelsCode0
Gaussian Process Subspace Regression for Model ReductionCode0
Adaptation of uncertainty-penalized Bayesian information criterion for parametric partial differential equation discoveryCode0
GeMID: Generalizable Models for IoT Device IdentificationCode0
GestureGPT: Toward Zero-Shot Free-Form Hand Gesture Understanding with Large Language Model AgentsCode0
Increasing certainty in systems biology models using Bayesian multimodel inferenceCode0
Finite Mixtures of Multivariate Poisson-Log Normal Factor Analyzers for Clustering Count DataCode0
Flexible, Non-parametric Modeling Using Regularized Neural NetworksCode0
FIESTA: Fast IdEntification of State-of-The-Art models using adaptive bandit algorithmsCode0
A survey of probabilistic generative frameworks for molecular simulationsCode0
Finding the Homology of Decision Boundaries with Active LearningCode0
FedScore: A privacy-preserving framework for federated scoring system developmentCode0
Algebraic Equivalence of Linear Structural Equation ModelsCode0
fETSmcs: Feature-based ETS model component selectionCode0
Supervised Models Can Generalize Also When Trained on Random LabelCode0
Fast Unsupervised Deep Outlier Model Selection with HypernetworksCode0
FiCo-ITR: bridging fine-grained and coarse-grained image-text retrieval for comparative performance analysisCode0
Fast and Informative Model Selection using Learning Curve Cross-ValidationCode0
Familia: An Open-Source Toolkit for Industrial Topic ModelingCode0
Fast Cross-Validation via Sequential TestingCode0
How Graph Structure and Label Dependencies Contribute to Node Classification in a Large Network of DocumentsCode0
Fair Enough: Standardizing Evaluation and Model Selection for Fairness Research in NLPCode0
Fairness and bias correction in machine learning for depression prediction: results from four study populationsCode0
Fast Instrument Learning with Faster RatesCode0
F1 is Not Enough! Models and Evaluation Towards User-Centered Explainable Question AnsweringCode0
Extremely Greedy Equivalence SearchCode0
Face Spoofing Detection using Deep LearningCode0
A Bayesian Modelling Framework with Model Comparison for Epidemics with Super-SpreadingCode0
Factored Latent-Dynamic Conditional Random Fields for Single and Multi-label Sequence ModelingCode0
Optimal design of experiments to identify latent behavioral typesCode0
A Human-in-the-Loop Fairness-Aware Model Selection Framework for Complex Fairness Objective LandscapesCode0
Exploring Human-in-the-Loop Test-Time Adaptation by Synergizing Active Learning and Model SelectionCode0
Execution-based Evaluation for Data Science Code Generation ModelsCode0
Exploring Design Choices for Building Language-Specific LLMsCode0
Exploring Model Transferability through the Lens of Potential EnergyCode0
Evaluation of HTR models without Ground Truth MaterialCode0
Evaluation of dynamic causal modelling and Bayesian model selection using simulations of networks of spiking neuronsCode0
Agreement-on-the-Line: Predicting the Performance of Neural Networks under Distribution ShiftCode0
Exploring Word Segmentation and Medical Concept Recognition for Chinese Medical TextsCode0
Evaluating Large Language Models as Generative User Simulators for Conversational RecommendationCode0
Estimating Individual Treatment Effects using Non-Parametric Regression Models: a ReviewCode0
Evaluating LLP Methods: Challenges and ApproachesCode0
E Pluribus Unum: Guidelines on Multi-Objective Evaluation of Recommender SystemsCode0
EPP: interpretable score of model predictive powerCode0
Differentiable Model Selection for Ensemble LearningCode0
MultiLink: Multi-class Structure Recovery via Agglomerative Clustering and Model SelectionCode0
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