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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 526–550 of 2050 papers

TitleStatusHype
Adaptive multi-penalty regularization based on a generalized Lasso pathCode0
Exploring Word Segmentation and Medical Concept Recognition for Chinese Medical TextsCode0
Exploring Design Choices for Building Language-Specific LLMsCode0
Exploring Human-in-the-Loop Test-Time Adaptation by Synergizing Active Learning and Model SelectionCode0
Bayesian Allocation Model: Inference by Sequential Monte Carlo for Nonnegative Tensor Factorizations and Topic Models using Polya UrnsCode0
Execution-based Evaluation for Data Science Code Generation ModelsCode0
Evaluation of HTR models without Ground Truth MaterialCode0
Evaluation of dynamic causal modelling and Bayesian model selection using simulations of networks of spiking neuronsCode0
Extremely Greedy Equivalence SearchCode0
Batch Value-function Approximation with Only RealizabilityCode0
An Evaluation Toolkit to Guide Model Selection and Cohort Definition in Causal InferenceCode0
An Empirical Study of Pre-trained Model Selection for Out-of-Distribution Generalization and CalibrationCode0
AxiomVision: Accuracy-Guaranteed Adaptive Visual Model Selection for Perspective-Aware Video AnalyticsCode0
Defining Expertise: Applications to Treatment Effect EstimationCode0
Estimating Individual Treatment Effects using Non-Parametric Regression Models: a ReviewCode0
Evaluating Large Language Models as Generative User Simulators for Conversational RecommendationCode0
E-QUARTIC: Energy Efficient Edge Ensemble of Convolutional Neural Networks for Resource-Optimized LearningCode0
Adaptive Mixtures of Factor AnalyzersCode0
DeepNNK: Explaining deep models and their generalization using polytope interpolationCode0
EPP: interpretable score of model predictive powerCode0
Evaluating LLP Methods: Challenges and ApproachesCode0
F1 is Not Enough! Models and Evaluation Towards User-Centered Explainable Question AnsweringCode0
Deep Weakly-Supervised Learning Methods for Classification and Localization in Histology Images: A SurveyCode0
Hybrid safe-strong rules for efficient optimization in lasso-type problemsCode0
Embarrassingly Simple Performance Prediction for Abductive Natural Language InferenceCode0
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