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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 251–275 of 2050 papers

TitleStatusHype
Automatic Componentwise Boosting: An Interpretable AutoML System—0
Automatic Debiased Machine Learning for Smooth Functionals of Nonparametric M-Estimands—0
Automatic Dimension Selection for a Non-negative Factorization Approach to Clustering Multiple Random Graphs—0
Automatic Double Reinforcement Learning in Semiparametric Markov Decision Processes with Applications to Long-Term Causal Inference—0
A Theory of Multiple-Source Adaptation with Limited Target Labeled Data—0
Exploring convolutional neural networks with transfer learning for diagnosing Lyme disease from skin lesion images—0
A Systematic Evaluation of Domain Adaptation Algorithms On Time Series Data—0
A Local Information Criterion for Dynamical Systems—0
Benchmarking Open-Source Large Language Models on Healthcare Text Classification Tasks—0
Asymptotics of the Bootstrap via Stability with Applications to Inference with Model Selection—0
Asymptotic Model Selection for Directed Networks with Hidden Variables—0
ALMERIA: Boosting pairwise molecular contrasts with scalable methods—0
Asymptotic Accuracy of Distribution-Based Estimation for Latent Variables—0
A Symmetry-based Framework for Model Selection of Coral Reef Population Growth Models—0
The Mismeasure of Man and Models: Evaluating Allocational Harms in Large Language Models—0
Beyond similarity assessment: Selecting the optimal model for sequence alignment via the Factorized Asymptotic Bayesian algorithm—0
Asymmetrically Weighted CCA And Hierarchical Kernel Sentence Embedding For Image & Text Retrieval—0
A Symbolic and Statistical Learning Framework to Discover Bioprocessing Regulatory Mechanism: Cell Culture Example—0
A linearized framework and a new benchmark for model selection for fine-tuning—0
A Survey on Theoretical Advances of Community Detection in Networks—0
eGAD! double descent is explained by Generalized Aliasing Decomposition—0
Active Nearest-Neighbor Learning in Metric Spaces—0
Bayesian Variable Selection for Globally Sparse Probabilistic PCA—0
A Survey of Machine Learning Methods and Challenges for Windows Malware Classification—0
A Survey of Learning Curves with Bad Behavior: or How More Data Need Not Lead to Better Performance—0
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