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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 326–350 of 2050 papers

TitleStatusHype
How Graph Structure and Label Dependencies Contribute to Node Classification in a Large Network of DocumentsCode0
Anytime Model Selection in Linear BanditsCode0
Fair Enough: Standardizing Evaluation and Model Selection for Fairness Research in NLPCode0
Fairness and bias correction in machine learning for depression prediction: results from four study populationsCode0
Fast Unsupervised Deep Outlier Model Selection with HypernetworksCode0
Flexible, Non-parametric Modeling Using Regularized Neural NetworksCode0
AnyLoss: Transforming Classification Metrics into Loss FunctionsCode0
Exploring Word Segmentation and Medical Concept Recognition for Chinese Medical TextsCode0
Extremely Greedy Equivalence SearchCode0
Exploring Design Choices for Building Language-Specific LLMsCode0
Execution-based Evaluation for Data Science Code Generation ModelsCode0
Exploring Human-in-the-Loop Test-Time Adaptation by Synergizing Active Learning and Model SelectionCode0
F1 is Not Enough! Models and Evaluation Towards User-Centered Explainable Question AnsweringCode0
BiasBed - Rigorous Texture Bias EvaluationCode0
BiasBed -- Rigorous Texture Bias EvaluationCode0
Evaluation of dynamic causal modelling and Bayesian model selection using simulations of networks of spiking neuronsCode0
Evaluation of HTR models without Ground Truth MaterialCode0
Evaluating Large Language Models as Generative User Simulators for Conversational RecommendationCode0
Big model only for hard audios: Sample dependent Whisper model selection for efficient inferencesCode0
Beyond One-Size-Fits-All: Tailored Benchmarks for Efficient EvaluationCode0
Evaluating LLP Methods: Challenges and ApproachesCode0
Exploring Model Transferability through the Lens of Potential EnergyCode0
A novel algebraic approach to time-reversible evolutionary modelsCode0
Face Spoofing Detection using Deep LearningCode0
A Normative Theory for Causal Inference and Bayes Factor Computation in Neural CircuitsCode0
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