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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 351–400 of 2050 papers

TitleStatusHype
Model Selection for Off-policy Evaluation: New Algorithms and Experimental Protocol—0
Optimality in importance sampling: a gentle survey—0
SMRS: advocating a unified reporting standard for surrogate models in the artificial intelligence era—0
The Value of Information in Human-AI Decision-making—0
Agentic AI Systems Applied to tasks in Financial Services: Modeling and model risk management crews—0
Mixture of neural operator experts for learning boundary conditions and model selection—0
Robust Knowledge Distillation in Federated Learning: Counteracting Backdoor AttacksCode0
A spectral clustering-type algorithm for the consistent estimation of the Hurst distribution in moderately high dimensions—0
Scaling Inference-Efficient Language Models—0
Vision-Language Model Selection and Reuse for Downstream Adaptation—0
DFPE: A Diverse Fingerprint Ensemble for Enhancing LLM PerformanceCode0
Data-Informed Model Complexity Metric for Optimizing Symbolic Regression Models—0
Dynamics of Transient Structure in In-Context Linear Regression Transformers—0
Quantifying Uncertainty and Variability in Machine Learning: Confidence Intervals for Quantiles in Performance Metric Distributions—0
Rethinking Foundation Models for Medical Image Classification through a Benchmark Study on MedMNIST—0
A Bayesian Modelling Framework with Model Comparison for Epidemics with Super-SpreadingCode0
Automatic Debiased Machine Learning for Smooth Functionals of Nonparametric M-Estimands—0
Principled model selection for stochastic dynamics—0
Statistical Inference for Sequential Feature Selection after Domain AdaptationCode0
Utilizing AI Language Models to Identify Prognostic Factors for Coronary Artery Disease: A Study in Mashhad Residents—0
Empowering Agricultural Insights: RiceLeafBD - A Novel Dataset and Optimal Model Selection for Rice Leaf Disease Diagnosis through Transfer Learning Technique—0
On the use of Statistical Learning Theory for model selection in Structural Health Monitoring—0
Fast sampling and model selection for Bayesian mixture models—0
An Investigation into Seasonal Variations in Energy Forecasting for Student Residences—0
Automatic Double Reinforcement Learning in Semiparametric Markov Decision Processes with Applications to Long-Term Causal Inference—0
A Comprehensive Evaluation of Large Language Models on Mental Illnesses in Arabic Context—0
Unsupervised detection and fitness estimation of emerging SARS-CoV-2 variants. Application to wastewater samples (ANRS0160)Code0
Private Selection with Heterogeneous Sensitivities—0
An Instrumental Variables Approach to Testing Firm Conduct—0
How to Select Pre-Trained Code Models for Reuse? A Learning Perspective—0
MODfinity: Unsupervised Domain Adaptation with Multimodal Information Flow Intertwining—0
Learning to Rank Pre-trained Vision-Language Models for Downstream Tasks—0
An Unsupervised Anomaly Detection in Electricity Consumption Using Reinforcement Learning and Time Series Forest Based Framework—0
Adversarial Negotiation Dynamics in Generative Language Models—0
Recommending Pre-Trained Models for IoT Devices—0
Structure Learning in Gaussian Graphical Models from Glauber Dynamics—0
Exploring Dynamic Novel View Synthesis Technologies for Cinematography—0
Know2Vec: A Black-Box Proxy for Neural Network RetrievalCode0
YOLOv11 Optimization for Efficient Resource UtilizationCode0
From Human Annotation to LLMs: SILICON Annotation Workflow for Management Research—0
Quantum Machine Learning in Log-based Anomaly Detection: Challenges and Opportunities—0
Investigating the Impact of Balancing, Filtering, and Complexity on Predictive Multiplicity: A Data-Centric PerspectiveCode0
Deep Clustering using Dirichlet Process Gaussian Mixture and Alpha Jensen-Shannon Divergence Clustering Loss—0
PyOD 2: A Python Library for Outlier Detection with LLM-powered Model Selection—0
Noncommutative Model Selection for Data Clustering and Dimension Reduction Using Relative von Neumann Entropy—0
Noncommutative Model Selection and the Data-Driven Estimation of Real Cohomology Groups—0
SPAgent: Adaptive Task Decomposition and Model Selection for General Video Generation and Editing—0
On the relative performance of some parametric and nonparametric estimators of option prices—0
Puzzle: Distillation-Based NAS for Inference-Optimized LLMs—0
Optimized Conformal Selection: Powerful Selective Inference After Conformity Score OptimizationCode0
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