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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 1101–1125 of 2050 papers

TitleStatusHype
Validate on Sim, Detect on Real -- Model Selection for Domain Randomization—0
We Need to Talk About train-dev-test SplitsCode0
Multivariate rank via entropic optimal transport: sample efficiency and generative modelingCode0
Event Data Association via Robust Model Fitting for Event-based Object Tracking—0
The Pareto Frontier of model selection for general Contextual Bandits—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
Show Me the Whole World: Towards Entire Item Space Exploration for Interactive Personalized RecommendationsCode0
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
A novel framework to quantify uncertainty in peptide-tandem mass spectrum matches with application to nanobody peptide identification—0
Finding Materialized Models for Model ReuseCode0
Topological Data Analysis (TDA) Techniques Enhance Hand Pose Classification from ECoG Neural Recordings—0
A Model Selection Approach for Corruption Robust Reinforcement Learning—0
AgFlow: Fast Model Selection of Penalized PCA via Implicit Regularization Effects of Gradient Flow—0
MPSN: Motion-aware Pseudo Siamese Network for Indoor Video Head Detection in BuildingsCode0
Post-hoc Models for Performance Estimation of Machine Learning Inference—0
Variance function estimation in regression model via aggregation procedures—0
Belief propagation for permutations, rankings, and partial orders—0
Empirical Quantitative Analysis of COVID-19 Forecasting Models—0
The Infinite Contextual Graph Markov Model—0
Gradient-based Hyperparameter Optimization without Validation Data for Learning fom Limited Labels—0
On the Uncomputability of Partition Functions in Energy-Based Sequence Models—0
A Systematic Evaluation of Domain Adaptation Algorithms On Time Series Data—0
Probability Distribution on Full Rooted Trees—0
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