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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 501–525 of 2050 papers

TitleStatusHype
Nonlinear Causal Discovery for Grouped Data—0
DataAssist: A Machine Learning Approach to Data Cleaning and Preparation—0
A novel framework to quantify uncertainty in peptide-tandem mass spectrum matches with application to nanobody peptide identification—0
Automatic Componentwise Boosting: An Interpretable AutoML System—0
Data-driven calibration of linear estimators with minimal penalties—0
Automatic Debiased Machine Learning for Smooth Functionals of Nonparametric M-Estimands—0
Data-Driven Learning of the Number of States in Multi-State Autoregressive Models—0
Data-driven model selection within the matrix completion method for causal panel data models—0
Data-Driven Online Model Selection With Regret Guarantees—0
Data-Efficient Pipeline for Offline Reinforcement Learning with Limited Data—0
Designing Ecosystems of Intelligence from First Principles—0
Selective machine learning of doubly robust functionals—0
Local Projections Inference with High-Dimensional Covariates without Sparsity—0
Designing Interpretable ML System to Enhance Trust in Healthcare: A Systematic Review to Proposed Responsible Clinician-AI-Collaboration Framework—0
Beyond similarity assessment: Selecting the optimal model for sequence alignment via the Factorized Asymptotic Bayesian algorithm—0
A Novel Approach to Eliminating Hallucinations in Large Language Model-Assisted Causal Discovery—0
A Comprehensive Evaluation of Large Language Models on Mental Illnesses in Arabic Context—0
Beyond One-Size-Fits-All: Multi-Domain, Multi-Task Framework for Embedding Model Selection—0
Beyond Glucose-Only Assessment: Advancing Nocturnal Hypoglycemia Prediction in Children with Type 1 Diabetes—0
A Dirichlet stochastic block model for composition-weighted networks—0
A Bandit Approach with Evolutionary Operators for Model Selection—0
Detecting Signs of Model Change with Continuous Model Selection Based on Descriptive Dimensionality—0
Beyond Conjugacy for Chain Event Graph Model Selection—0
AaltoNLP at SemEval-2022 Task 11: Ensembling Task-adaptive Pretrained Transformers for Multilingual Complex NER—0
Deriving Emotions and Sentiments from Visual Content: A Disaster Analysis Use Case—0
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