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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 601–625 of 2050 papers

TitleStatusHype
Bayesian Model Selection Approach to Boundary Detection with Non-Local Priors—0
Disentangling Factors of Variations Using Few Labels—0
Disentangling Factors of Variation Using Few Labels—0
Distributed Bayesian Piecewise Sparse Linear Models—0
Distributed filtered hyperinterpolation for noisy data on the sphere—0
An HMM Approach with Inherent Model Selection for Sign Language and Gesture Recognition—0
An Information-Theoretic Approach to Transferability in Task Transfer Learning—0
Distribution-free Deviation Bounds and The Role of Domain Knowledge in Learning via Model Selection with Cross-validation Risk Estimation—0
Bayesian Nonparametrics: An Alternative to Deep Learning—0
DIVE: Subgraph Disagreement for Graph Out-of-Distribution Generalization—0
Digital Twin-Assisted Knowledge Distillation Framework for Heterogeneous Federated Learning—0
Domain adaptation in practice: Lessons from a real-world information extraction pipeline—0
Domain-Specific Retrieval-Augmented Generation Using Vector Stores, Knowledge Graphs, and Tensor Factorization—0
Dominant Drivers of National Inflation—0
Bayesian Optimization Over Iterative Learners with Structured Responses: A Budget-aware Planning Approach—0
Dual-stage optimizer for systematic overestimation adjustment applied to multi-objective genetic algorithms for biomarker selection—0
Double/Debiased Machine Learning for Dynamic Treatment Effects via g-Estimation—0
Double Machine Learning and Automated Confounder Selection -- A Cautionary Tale—0
Doubly robust off-policy evaluation with shrinkage—0
Downstream Task-Oriented Generative Model Selections on Synthetic Data Training for Fraud Detection Models—0
DiffusionGPT: LLM-Driven Text-to-Image Generation System—0
Bayesian Robust Tensor Factorization for Incomplete Multiway Data—0
Bayesian leave-one-out cross-validation for large data—0
DSDE: Using Proportion Estimation to Improve Model Selection for Out-of-Distribution Detection—0
Bayesian Learning with Wasserstein Barycenters—0
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