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 1601–1625 of 2050 papers

TitleStatusHype
Model Selection for Generalized Zero-shot Learning—0
Reinforcement Learning based Dynamic Model Selection for Short-Term Load Forecasting—0
Learning stable and predictive structures in kinetic systems: Benefits of a causal approach—0
Model Selection for Nonnegative Matrix Factorization by Support Union Recovery—0
On The Stability of Interpretable Models—0
Model Selection Techniques -- An Overview—0
MS-BACO: A new Model Selection algorithm using Binary Ant Colony Optimization for neural complexity and error reduction—0
Variational Bayesian Monte CarloCode1
A Unified Dynamic Approach to Sparse Model Selection—0
Find the dimension that counts: Fast dimension estimation and Krylov PCA—0
Cost-Sensitive Learning for Predictive Maintenance—0
A User-based Visual Analytics Workflow for Exploratory Model Analysis—0
Lexical Bias In Essay Level Prediction—0
Improving Subseasonal Forecasting in the Western U.S. with Machine LearningCode0
Comparison between Suitable Priors for Additive Bayesian Networks—0
Bayesian Structure Learning by Recursive Bootstrap—0
Bayesian sparse reconstruction: a brute-force approach to astronomical imaging and machine learningCode0
Simultaneous Localization and Layout Model Selection in Manhattan Worlds—0
Tensor Ring Decomposition with Rank Minimization on Latent Space: An Efficient Approach for Tensor Completion—0
View-graph Selection Framework for SfM—0
Data-driven discovery of PDEs in complex datasetsCode0
A Survey on Theoretical Advances of Community Detection in Networks—0
Parameter-wise co-clustering for high-dimensional data—0
Multiclass Universum SVMCode0
On an improvement of LASSO by scaling—0
Show:102550
← PrevPage 65 of 82Next →

No leaderboard results yet.