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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 1701–1750 of 2050 papers

TitleStatusHype
Scalable Ensemble Diversification for OOD Generalization and DetectionCode0
Conformal online model aggregationCode0
Parsimonious Bayesian deep networksCode0
FedScore: A privacy-preserving framework for federated scoring system developmentCode0
Scalable Marginal Likelihood Estimation for Model Selection in Deep LearningCode0
fETSmcs: Feature-based ETS model component selectionCode0
Subject-driven Text-to-Image Generation via Preference-based Reinforcement LearningCode0
Parsimony-Enhanced Sparse Bayesian Learning for Robust Discovery of Partial Differential EquationsCode0
FiCo-ITR: bridging fine-grained and coarse-grained image-text retrieval for comparative performance analysisCode0
FIESTA: Fast IdEntification of State-of-The-Art models using adaptive bandit algorithmsCode0
Finding the Homology of Decision Boundaries with Active LearningCode0
Partially Hidden Markov Chain Linear Autoregressive model: inference and forecastingCode0
Valid causal inference with unobserved confounding in high-dimensional settingsCode0
Finite Mixtures of Multivariate Poisson-Log Normal Factor Analyzers for Clustering Count DataCode0
Effective Stabilized Self-Training on Few-Labeled Graph DataCode0
Pass off Fish Eyes for Pearls: Attacking Model Selection of Pre-trained ModelsCode0
Model selection and parameter inference in phylogenetics using Nested SamplingCode0
Unsupervised detection and fitness estimation of emerging SARS-CoV-2 variants. Application to wastewater samples (ANRS0160)Code0
Patched RTC: evaluating LLMs for diverse software development tasksCode0
Flexible, Non-parametric Modeling Using Regularized Neural NetworksCode0
SubStrat: A Subset-Based Strategy for Faster AutoMLCode0
AnyLoss: Transforming Classification Metrics into Loss FunctionsCode0
Dynamic Interpretability for Model Comparison via Decision RulesCode0
Unsupervised Discretization by Two-dimensional MDL-based HistogramCode0
CaloFlow: Fast and Accurate Generation of Calorimeter Showers with Normalizing FlowsCode0
DSV: An Alignment Validation Loss for Self-supervised Outlier Model SelectionCode0
Driver Identification by an Ensemble of CNNs Obtained from Majority-Voting Model SelectionCode0
Model Selection for Bayesian AutoencodersCode0
To token or not to token: A Comparative Study of Text Representations for Cross-Lingual TransferCode0
Free Lunch: Robust Cross-Lingual Transfer via Model Checkpoint AveragingCode0
Automated Model Selection for Tabular DataCode0
Model Selection for Cross-Lingual TransferCode0
Scikit-learn: Machine Learning in PythonCode0
Tune: A Research Platform for Distributed Model Selection and TrainingCode0
Phase Transitions and a Model Order Selection Criterion for Spectral Graph ClusteringCode0
Don't Waste Your Time: Early Stopping Cross-ValidationCode0
Achieving Well-Informed Decision-Making in Drug Discovery: A Comprehensive Calibration Study using Neural Network-Based Structure-Activity ModelsCode0
GA-PARSIMONY: A GA-SVR approach with feature selection and parameter optimization to obtain parsimonious solutions for predicting temperature settings in a continuous annealing furnaceCode0
MetaGL: Evaluation-Free Selection of Graph Learning Models via Meta-LearningCode0
What the HellaSwag? On the Validity of Common-Sense Reasoning BenchmarksCode0
Bolasso: model consistent Lasso estimation through the bootstrapCode0
Towards Accurate Model Selection in Deep Unsupervised Domain AdaptationCode0
Gaussian Process Subspace Regression for Model ReductionCode0
GeMID: Generalizable Models for IoT Device IdentificationCode0
Big model only for hard audios: Sample dependent Whisper model selection for efficient inferencesCode0
Conditional Density Estimation Tools in Python and R with Applications to Photometric Redshifts and Likelihood-Free Cosmological InferenceCode0
Generalised Linear Models for Dependent Binary Outcomes with Applications to Household Stratified Pandemic Influenza DataCode0
Por Qué Não Utiliser Alla Språk? Mixed Training with Gradient Optimization in Few-Shot Cross-Lingual TransferCode0
SecretGen: Privacy Recovery on Pre-Trained Models via Distribution DiscriminationCode0
Symmetric Linear Bandits with Hidden SymmetryCode0
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