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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 401–450 of 2050 papers

TitleStatusHype
Choice of V for V-Fold Cross-Validation in Least-Squares Density Estimation—0
Choosing a Model, Shaping a Future: Comparing LLM Perspectives on Sustainability and its Relationship with AI—0
An Unsupervised Anomaly Detection in Electricity Consumption Using Reinforcement Learning and Time Series Forest Based Framework—0
A simple application of FIC to model selection—0
CLAMS: A System for Zero-Shot Model Selection for Clustering—0
Classification of MRI data using Deep Learning and Gaussian Process-based Model Selection—0
Classification Performance Metric for Imbalance Data Based on Recall and Selectivity Normalized in Class Labels—0
Classification with Scattering Operators—0
Classification with Sparse Overlapping Groups—0
client2vec: Towards Systematic Baselines for Banking Applications—0
AssistedDS: Benchmarking How External Domain Knowledge Assists LLMs in Automated Data Science—0
Clipper: A Low-Latency Online Prediction Serving System—0
A Comprehensive Sustainable Framework for Machine Learning and Artificial Intelligence—0
Closing the gap between open-source and commercial large language models for medical evidence summarization—0
Binary Matrix Factorization via Dictionary Learning—0
An Overview of Human Activity Recognition Using Wearable Sensors: Healthcare and Artificial Intelligence—0
A Novel Parameter-Tying Theorem in Multi-Model Adaptive Systems: Systematic Approach for Efficient Model Selection—0
Clustering evolving data using kernel-based methods—0
A Statistical Framework for Model Selection in LSTM Networks—0
Clustering - What Both Theoreticians and Practitioners are Doing Wrong—0
Clustering with Fast, Automated and Reproducible assessment applied to longitudinal neural tracking—0
CMA-ES for Post Hoc Ensembling in AutoML: A Great Success and Salvageable Failure—0
biastest: Testing parameter equality across different models in Stata—0
Cognito: Automated Feature Engineering for Supervised Learning—0
A Strong Baseline for Batch Imitation Learning—0
Collab: Controlled Decoding using Mixture of Agents for LLM Alignment—0
Collaborative-controlled LASSO for Constructing Propensity Score-based Estimators in High-Dimensional Data—0
Collaborative Deep Learning for Speech Enhancement: A Run-Time Model Selection Method Using Autoencoders—0
Combinatorially Generated Piecewise Activation Functions—0
Combined l_1 and greedy l_0 penalized least squares for linear model selection—0
Advanced Financial Reasoning at Scale: A Comprehensive Evaluation of Large Language Models on CFA Level III—0
Combining Linear Non-Gaussian Acyclic Model with Logistic Regression Model for Estimating Causal Structure from Mixed Continuous and Discrete Data—0
Coupled differentiation and division of embryonic stem cells inferred from clonal snapshots—0
A Latent Gaussian Mixture Model for Clustering Longitudinal Data—0
Communication-efficient Distributed Sparse Linear Discriminant Analysis—0
Comparative Analysis of Data Preprocessing Methods, Feature Selection Techniques and Machine Learning Models for Improved Classification and Regression Performance on Imbalanced Genetic Data—0
Comparative Analysis of LSTM Neural Networks and Traditional Machine Learning Models for Predicting Diabetes Patient Readmission—0
Comparative Analysis of Predicting Subsequent Steps in Hénon Map—0
Cox process representation and inference for stochastic reaction-diffusion processes—0
A novel efficient Multi-view traffic-related object detection framework—0
A novel framework to quantify uncertainty in peptide-tandem mass spectrum matches with application to nanobody peptide identification—0
Comparative Study of Machine Learning Algorithms in Detecting Cardiovascular Diseases—0
Comparing Bayesian Models of Annotation—0
Comparison between Suitable Priors for Additive Bayesian Networks—0
Asymmetrically Weighted CCA And Hierarchical Kernel Sentence Embedding For Image & Text Retrieval—0
Comparison of Bayesian predictive methods for model selection—0
Cost-Effective Online Contextual Model Selection—0
Selective machine learning of doubly robust functionals—0
Complex decision-making strategies in a stock market experiment explained as the combination of few simple strategies—0
Local Projections Inference with High-Dimensional Covariates without Sparsity—0
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