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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 1026–1050 of 2050 papers

TitleStatusHype
Validate on Sim, Detect on Real -- Model Selection for Domain Randomization—0
Multivariate rank via entropic optimal transport: sample efficiency and generative modelingCode0
Simple data balancing achieves competitive worst-group-accuracyCode1
The Pareto Frontier of model selection for general Contextual Bandits—0
mlr3spatiotempcv: Spatiotemporal resampling methods for machine learning in RCode1
Event Data Association via Robust Model Fitting for Event-based Object Tracking—0
Fast and Accurate Graph Learning for Huge Data via Minipatch Ensembles—0
DMS, AE, DAA: methods and applications of adaptive time series model selection, ensemble, and financial evaluationCode0
Ensemble of Averages: Improving Model Selection and Boosting Performance in Domain GeneralizationCode1
Show Me the Whole World: Towards Entire Item Space Exploration for Interactive Personalized RecommendationsCode0
abess: A Fast Best Subset Selection Library in Python and RCode1
A Nested Weighted Tchebycheff Multi-Objective Bayesian Optimization Approach for Flexibility of Unknown Utopia Estimation in Expensive Black-box Design Problems—0
On Model Selection Consistency of Lasso for High-Dimensional Ising Models—0
Hydra: A System for Large Multi-Model Deep LearningCode1
A novel framework to quantify uncertainty in peptide-tandem mass spectrum matches with application to nanobody peptide identification—0
UniPELT: A Unified Framework for Parameter-Efficient Language Model TuningCode1
Finding Materialized Models for Model ReuseCode0
Topological Data Analysis (TDA) Techniques Enhance Hand Pose Classification from ECoG Neural Recordings—0
MPSN: Motion-aware Pseudo Siamese Network for Indoor Video Head Detection in BuildingsCode0
AgFlow: Fast Model Selection of Penalized PCA via Implicit Regularization Effects of Gradient Flow—0
A Model Selection Approach for Corruption Robust Reinforcement Learning—0
RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random ForestsCode1
Variance function estimation in regression model via aggregation procedures—0
Post-hoc Models for Performance Estimation of Machine Learning Inference—0
Empirical Quantitative Analysis of COVID-19 Forecasting Models—0
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