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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 901–925 of 2050 papers

TitleStatusHype
Understanding the double descent curve in Machine Learning—0
GRASMOS: Graph Signage Model Selection for Gene Regulatory Networks—0
Execution-based Evaluation for Data Science Code Generation ModelsCode0
Sensitivity to control signals in triphasic rhythmic neural systems: a comparative mechanistic analysis via infinitesimal local timing response curves—0
MGTCOM: Community Detection in Multimodal GraphsCode0
Fairness and bias correction in machine learning for depression prediction: results from four study populationsCode0
Robust Model Selection of Gaussian Graphical Models—0
Beyond Conjugacy for Chain Event Graph Model Selection—0
Sparse Gaussian Process Hyperparameters: Optimize or Integrate?—0
Oracle Inequalities for Model Selection in Offline Reinforcement Learning—0
An Information-Theoretic Approach for Estimating Scenario Generalization in Crowd Motion Prediction—0
Differentiable Model Selection for Ensemble LearningCode0
Estimation of Heterogeneous Treatment Effects Using a Conditional Moment Based Approach—0
TRScore: A Novel GPT-based Readability Scorer for ASR Segmentation and Punctuation model evaluation and selection—0
Which is the best model for my data?—0
Improving Group Lasso for high-dimensional categorical data—0
Post-Selection Confidence Bounds for Prediction PerformanceCode0
Structural Kernel Search via Bayesian Optimization and Symbolical Optimal TransportCode0
Scalable Bayesian Transformed Gaussian Processes—0
Measures of Information Reflect Memorization Patterns—0
Data-Efficient Pipeline for Offline Reinforcement Learning with Limited Data—0
LEATHER: A Framework for Learning to Generate Human-like Text in DialogueCode0
On the calibration of underrepresented classes in LiDAR-based semantic segmentation—0
Synthetic Model Combination: An Instance-wise Approach to Unsupervised Ensemble LearningCode0
To tree or not to tree? Assessing the impact of smoothing the decision boundaries—0
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