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 1801–1825 of 2050 papers

TitleStatusHype
The Shallow End: Empowering Shallower Deep-Convolutional Networks through Auxiliary OutputsCode0
Analyzing Framing through the Casts of Characters in the News—0
Inertial Regularization and Selection (IRS): Sequential Regression in High-Dimension and Sparsity—0
Gaussian process modeling in approximate Bayesian computation to estimate horizontal gene transfer in bacteria—0
Robust and Parallel Bayesian Model Selection—0
Generalization error minimization: a new approach to model evaluation and selection with an application to penalized regression—0
Going off the Grid: Iterative Model Selection for Biclustered Matrix Completion—0
Detection of intensity bursts using Hawkes processes: an application to high frequency financial data—0
Communication-efficient Distributed Sparse Linear Discriminant Analysis—0
Nonparametric Bayesian inference of the microcanonical stochastic block model—0
Model Selection for Gaussian Process Regression by Approximation Set Coding—0
Searching parsimonious solutions with GA-PARSIMONY and XGboost in high-dimensional databases—0
Universum Learning for Multiclass SVM—0
Robust Regression For Image Binarization Under Heavy Noises and Nonuniform Background—0
Learning conditional independence structure for high-dimensional uncorrelated vector processes—0
GTApprox: surrogate modeling for industrial designCode0
Feedback-Controlled Sequential Lasso Screening—0
Large-scale Collaborative Imaging Genetics Studies of Risk Genetic Factors for Alzheimer's Disease Across Multiple Institutions—0
Bayesian Model Selection Methods for Mutual and Symmetric k-Nearest Neighbor Classification—0
Learning Dynamic Hierarchical Models for Anytime Scene Labeling—0
Iterative Hard Thresholding for Model Selection in Genome-Wide Association StudiesCode0
UniTN End-to-End Discourse Parser for CoNLL 2016 Shared Task—0
Using Kernel Methods and Model Selection for Prediction of Preterm Birth—0
Superpixel-based Two-view Deterministic Fitting for Multiple-structure Data—0
Incremental Learning for Fully Unsupervised Word Segmentation Using Penalized Likelihood and Model Selection—0
Show:102550
← PrevPage 73 of 82Next →

No leaderboard results yet.