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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
Tryage: Real-time, intelligent Routing of User Prompts to Large Language Models—0
Adaptive Uncertainty-Guided Model Selection for Data-Driven PDE DiscoveryCode0
Open, Closed, or Small Language Models for Text Classification?—0
Which Transformer to Favor: A Comparative Analysis of Efficiency in Vision TransformersCode1
LCE: An Augmented Combination of Bagging and Boosting in PythonCode1
No Regularization is Needed: An Efficient and Effective Model for Incomplete Label Distribution Learning—0
Foundation Model is Efficient Multimodal Multitask Model SelectorCode1
A coupled-mechanisms modelling framework for neurodegeneration—0
Updating Clinical Risk Stratification Models Using Rank-Based Compatibility: Approaches for Evaluating and Optimizing Clinician-Model Team Performance—0
Cal-SFDA: Source-Free Domain-adaptive Semantic Segmentation with Differentiable Expected Calibration ErrorCode1
Understanding User Intent Modeling for Conversational Recommender Systems: A Systematic Literature Review—0
A Review of Change of Variable Formulas for Generative Modeling—0
Interpretable Machine Learning for Discovery: Statistical Challenges \& Opportunities—0
A Study of Unsupervised Evaluation Metrics for Practical and Automatic Domain Adaptation—0
Predictive Modeling through Hyper-Bayesian Optimization—0
A Critical Review of Large Language Models: Sensitivity, Bias, and the Path Toward Specialized AI—0
An Ensemble Method of Deep Reinforcement Learning for Automated Cryptocurrency Trading—0
Learning Disentangled Discrete RepresentationsCode0
Rational kernel-based interpolation for complex-valued frequency response functions—0
Anytime Model Selection in Linear BanditsCode0
Consistent model selection in the spiked Wigner model via AIC-type criteria—0
Adaptive debiased machine learning using data-driven model selection techniques—0
Fast Unsupervised Deep Outlier Model Selection with HypernetworksCode0
Self-Compatibility: Evaluating Causal Discovery without Ground TruthCode1
Towards a performance analysis on pre-trained Visual Question Answering models for autonomous drivingCode0
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