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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 1351–1400 of 2050 papers

TitleStatusHype
Systematic Ensemble Model Selection Approach for Educational Data Mining—0
Robust Lasso-Zero for sparse corruption and model selection with missing covariatesCode0
The scalable Birth-Death MCMC Algorithm for Mixed Graphical Model Learning with Application to Genomic Data IntegrationCode0
Lossy Compression with Distortion Constrained Optimization—0
Spiking Neural Networks Hardware Implementations and Challenges: a Survey—0
A Concise yet Effective model for Non-Aligned Incomplete Multi-view and Missing Multi-label LearningCode1
BayesOpt Adversarial AttackCode1
Disentangling Factors of Variations Using Few Labels—0
TopicNet: Making Additive Regularisation for Topic Modelling AccessibleCode0
An HMM Approach with Inherent Model Selection for Sign Language and Gesture Recognition—0
Recurrent neural networks and Koopman-based frameworks for temporal predictions in a low-order model of turbulence—0
DriveML: An R Package for Driverless Machine LearningCode1
Automatic Catalog of RRLyrae from 14 million VVV Light Curves: How far can we go with traditional machine-learning?Code0
Don't Use English Dev: On the Zero-Shot Cross-Lingual Evaluation of Contextual Embeddings—0
The Curse of Performance Instability in Analysis Datasets: Consequences, Source, and SuggestionsCode0
Coupled differentiation and division of embryonic stem cells inferred from clonal snapshots—0
Adaptive model selection in photonic reservoir computing by reinforcement learning—0
Counterfactual Learning of Stochastic Policies with Continuous Actions: from Models to Offline EvaluationCode1
Boxer: Interactive Comparison of Classifier Results—0
Contextual-Bandit Anomaly Detection for IoT Data in Distributed Hierarchical Edge Computing—0
Reliable Time Prediction in the Markov Stochastic Block ModelCode0
SINDy-PI: A Robust Algorithm for Parallel Implicit Sparse Identification of Nonlinear DynamicsCode1
Inferring Network Structure From Data—0
Evaluation of Model Selection for Kernel Fragment Recognition in Corn Silage—0
Dataless Model Selection with the Deep Frame Potential—0
Towards Stable and Comprehensive Domain Alignment: Max-Margin Domain-Adversarial Training—0
Introduction to Rare-Event Predictive Modeling for Inferential Statisticians -- A Hands-On Application in the Prediction of Breakthrough PatentsCode0
Optimization of Genomic Classifiers for Clinical Deployment: Evaluation of Bayesian Optimization to Select Predictive Models of Acute Infection and In-Hospital Mortality—0
Dimension Independent Generalization Error by Stochastic Gradient Descent—0
ARDA: Automatic Relational Data Augmentation for Machine LearningCode0
Structural-constrained Methods for the Identification of Unobservable False Data Injection Attacks in Power Systems—0
Clustering with Fast, Automated and Reproducible assessment applied to longitudinal neural tracking—0
DEPARA: Deep Attribution Graph for Deep Knowledge TransferabilityCode1
Deep Learning Algorithms for Rotating Machinery Intelligent Diagnosis: An Open Source Benchmark StudyCode1
Modeling User Behaviors in Machine Operation Tasks for Adaptive Guidance—0
A new approach in model selection for ordinal target variables—0
Rethinking Parameter Counting in Deep Models: Effective Dimensionality RevisitedCode1
Model Selection in Contextual Stochastic Bandit Problems—0
Approximate Cross-validation: Guarantees for Model Assessment and SelectionCode0
Determination of Latent Dimensionality in International Trade Flow—0
Robust-Adaptive Control of Linear Systems: beyond Quadratic Costs—0
Learning Gaussian Graphical Models via Multiplicative Weights—0
Double/Debiased Machine Learning for Dynamic Treatment Effects via g-Estimation—0
Impact of ImageNet Model Selection on Domain AdaptationCode0
Accelerating Psychometric Screening Tests With Bayesian Active Differential Selection—0
Deriving Emotions and Sentiments from Visual Content: A Disaster Analysis Use Case—0
Learning the Hypotheses Space from data Part II: Convergence and Feasibility—0
Blocked Clusterwise Regression—0
LIBTwinSVM: A Library for Twin Support Vector MachinesCode1
Learning the Hypotheses Space from data: Learning Space and U-curve Property—0
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