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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 1401–1450 of 2050 papers

TitleStatusHype
Marked point processes and intensity ratios for limit order book modeling—0
The Reciprocal Bayesian LASSOCode0
MetaSelector: Meta-Learning for Recommendation with User-Level Adaptive Model Selection—0
Oracle Efficient Estimation of Structural Breaks in Cointegrating Regressions—0
Evaluating Weakly Supervised Object Localization Methods RightCode1
SEERL: Sample Efficient Ensemble Reinforcement Learning—0
Stepwise Model Selection for Sequence Prediction via Deep Kernel Learning—0
Inferring Convolutional Neural Networks' accuracies from their architectural characterizationsCode0
Source Model Selection for Deep Learning in the Time Series DomainCode1
Understanding and Estimating the Adaptability of Domain-Invariant Representations—0
InfoGAN-CR: Disentangling Generative Adversarial Networks with Contrastive RegularizersCode1
On hyperparameter tuning in general clustering problemsm—0
Meta-Learning PAC-Bayes Priors in Model Averaging—0
An adaptive simulated annealing EM algorithm for inference on non-homogeneous hidden Markov modelsCode0
Bayesian high-dimensional linear regression with generic spike-and-slab priors—0
Learning high-dimensional probability distributions using tree tensor networks—0
Noise Fit, Estimation Error and a Sharpe Information Criterion—0
Forward and Backward Feature Selection for Query Performance Prediction—0
Bayesian Model Selection for Change Point Detection and Clustering—0
Automated Dependence PlotsCode0
Multiclass Learning from ContradictionsCode0
A Normative Theory for Causal Inference and Bayes Factor Computation in Neural CircuitsCode0
On model selection for scalable time series forecasting in transport networks—0
Generalised Linear Models for Dependent Binary Outcomes with Applications to Household Stratified Pandemic Influenza DataCode0
Improving Model Robustness Using Causal Knowledge—0
Combining human cell line transcriptome analysis and Bayesian inference to build trustworthy machine learning models for prediction of animal toxicity in drug development—0
Optimizing Deep Learning Inference on Embedded Systems Through Adaptive Model Selection—0
Factored Latent-Dynamic Conditional Random Fields for Single and Multi-label Sequence ModelingCode0
A multiple testing framework for diagnostic accuracy studies with co-primary endpointsCode0
Selective machine learning of doubly robust functionals—0
One Network to Segment Them All: A General, Lightweight System for Accurate 3D Medical Image SegmentationCode1
Framework for Inferring Following Strategies from Time Series of Movement DataCode0
Global Adaptive Generative Adjustment—0
Enhancing Certifiable Robustness via a Deep Model Ensemble—0
PT-MMD: A Novel Statistical Framework for the Evaluation of Generative Systems—0
Structure Learning of Gaussian Markov Random Fields with False Discovery Rate Control—0
Model selection for deep audio source separation via clustering analysis—0
Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles—0
hv-Block Cross Validation is not a BIBD: a Note on the Paper by Jeff Racine (2000)—0
A Unified Framework for Tuning Hyperparameters in Clustering Problems—0
Bayesian Model Selection for Identifying Markov Equivalent Causal Graphs—0
ExpertMatcher: Automating ML Model Selection for Clients using Hidden Representations—0
Gaussian Mixture Clustering Using Relative Tests of Fit—0
Effective Stabilized Self-Training on Few-Labeled Graph DataCode0
Distributed filtered hyperinterpolation for noisy data on the sphere—0
ExpertMatcher: Automating ML Model Selection for Users in Resource Constrained Countries—0
Model Order Selection Based on Information Theoretic Criteria: Design of the Penalty—0
Exploiting BERT for End-to-End Aspect-based Sentiment AnalysisCode1
ConfusionFlow: A model-agnostic visualization for temporal analysis of classifier confusion—0
Rejoinder on: Minimal penalties and the slope heuristics: a survey—0
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