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 1726–1750 of 2050 papers

TitleStatusHype
Ease.ml: Towards Multi-tenant Resource Sharing for Machine Learning Workloads—0
Evasion Attacks against Machine Learning at Test Time—0
Network Model Selection for Task-Focused Attributed Network Inference—0
Fixed effects testing in high-dimensional linear mixed models—0
Automatic Selection of t-SNE Perplexity—0
When Is the First Spurious Variable Selected by Sequential Regression Procedures?—0
Using Deep Neural Networks to Automate Large Scale Statistical Analysis for Big Data Applications—0
Neural Vector Spaces for Unsupervised Information RetrievalCode0
Data-driven Advice for Applying Machine Learning to Bioinformatics ProblemsCode0
Nonparametric weighted stochastic block models—0
Dirichlet Bayesian Network Scores and the Maximum Relative Entropy Principle—0
Sparse model selection via integral terms—0
LIMSI@CoNLL'17: UD Shared Task—0
Robust Gaussian Graphical Model Estimation with Arbitrary Corruption—0
FA3L at SemEval-2017 Task 3: A ThRee Embeddings Recurrent Neural Network for Question Answering—0
UdL at SemEval-2017 Task 1: Semantic Textual Similarity Estimation of English Sentence Pairs Using Regression Model over Pairwise FeaturesCode0
Consistent Nonparametric Different-Feature Selection via the Sparsest k-Subgraph Problem—0
Probabilistic models of individual and collective animal behavior—0
Familia: An Open-Source Toolkit for Industrial Topic ModelingCode0
Boosted Zero-Shot Learning with Semantic Correlation Regularization—0
Graphical posterior predictive classifier: Bayesian model averaging with particle GibbsCode0
Variational approach for learning Markov processes from time series data—0
Comparative Study of Inference Methods for Bayesian Nonnegative Matrix FactorisationCode0
Model Selection for Anomaly Detection—0
CHARDA: Causal Hybrid Automata Recovery via Dynamic AnalysisCode0
Show:102550
← PrevPage 70 of 82Next →

No leaderboard results yet.