SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1301–1325 of 2050 papers

TitleStatusHype
An Asymptotically Optimal Multi-Armed Bandit Algorithm and Hyperparameter OptimizationCode1
Behavioral analysis of support vector machine classifier with Gaussian kernel and imbalanced data—0
Model-based Clustering using Automatic Differentiation: Confronting Misspecification and High-Dimensional DataCode0
Robust pricing and hedging via neural SDEsCode1
Evaluation for Weakly Supervised Object Localization: Protocol, Metrics, and DatasetsCode1
Estimating Generalization under Distribution Shifts via Domain-Invariant RepresentationsCode1
Learning the Markov order of paths in a network—0
Deep learning for scene recognition from visual data: a survey—0
Learning with tree tensor networks: complexity estimates and model selection—0
In Search of Lost Domain GeneralizationCode1
Surveying Off-Board and Extra-Vehicular Monitoring and Progress Towards Pervasive Diagnostics—0
ANA at SemEval-2020 Task 4: mUlti-task learNIng for cOmmonsense reasoNing (UNION)Code0
The huge Package for High-dimensional Undirected Graph Estimation in R—0
Statistical inference of assortative community structures—0
Classification Performance Metric for Imbalance Data Based on Recall and Selectivity Normalized in Class Labels—0
Model family selection for classification using Neural Decision Trees—0
Open Problem: Model Selection for Contextual Bandits—0
Offline detection of change-points in the mean for stationary graph signalsCode0
Selecting Diverse Models for Scientific Insight—0
Towards an Unsupervised Method for Model Selection in Few-Shot Learning—0
Hidden Markov Models Applied To Intraday Momentum Trading With Side Information—0
A Survey of Machine Learning Methods and Challenges for Windows Malware Classification—0
Assumption-lean inference for generalised linear model parametersCode1
Selecting the Number of Clusters K with a Stability Trade-off: an Internal Validation CriterionCode1
TensorFlow with user friendly Graphical Framework for object detection APICode1
Show:102550
← PrevPage 53 of 82Next →

No leaderboard results yet.