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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 851–900 of 2050 papers

TitleStatusHype
Choice modelling in the age of machine learning - discussion paper—0
A Rule-Based Epidemiological Modelling Framework—0
Graph-based regularization for regression problems with alignment and highly-correlated designs—0
Graph Coding for Model Selection and Anomaly Detection in Gaussian Graphical Models—0
Graphical LASSO Based Model Selection for Time Series—0
A Critical Review of Large Language Models: Sensitivity, Bias, and the Path Toward Specialized AI—0
Graph Similarity Description: How Are These Graphs Similar?—0
Graph vs. Sequence: An Empirical Study on Knowledge Forms for Knowledge-Grounded Dialogue—0
GRASMOS: Graph Signage Model Selection for Gene Regulatory Networks—0
Greedy equivalence search for nonparametric graphical models—0
Greedy metrics in orthogonal greedy learning—0
Greedy Model Averaging—0
A Bayesian constitutive model selection framework for biaxial mechanical testing of planar soft tissues: application to porcine aortic valves—0
Green Runner: A tool for efficient deep learning component selection—0
Green Runner: A tool for efficient model selection from model repositories—0
GRIDS: Grouped Multiple-Degradation Restoration with Image Degradation Similarity—0
Fitting very flexible models: Linear regression with large numbers of parameters—0
Fitting Sparse Markov Models to Categorical Time Series Using Regularization—0
Fitting Multiple Heterogeneous Models by Multi-Class Cascaded T-Linkage—0
Guided Sampling-based Evolutionary Deep Neural Network for Intelligent Fault Diagnosis—0
Artificial neural network based modelling approach for municipal solid waste gasification in a fluidized bed reactor—0
Fine-Tuning Video Transformers for Word-Level Bangla Sign Language: A Comparative Analysis for Classification Tasks—0
Handling Symbolic Language in Student Texts: A Comparative Study of NLP Embedding Models—0
Has the Creativity of Large-Language Models peaked? An analysis of inter- and intra-LLM variability—0
Hate Speech and Offensive Content Detection in Indo-Aryan Languages: A Battle of LSTM and Transformers—0
Find the dimension that counts: Fast dimension estimation and Krylov PCA—0
Have we been Naive to Select Machine Learning Models? Noisy Data are here to Stay!—0
EdgeSight: Enabling Modeless and Cost-Efficient Inference at the Edge—0
Arrival Time Prediction for Autonomous Shuttle Services in the Real World: Evidence from Five Cities—0
Agreement-based Learning—0
FIB: A Method for Evaluation of Feature Impact Balance in Multi-Dimensional Data—0
Hierarchical Block Structures and High-resolution Model Selection in Large Networks—0
Few-shot Adaptation of Multi-modal Foundation Models: A Survey—0
Causal Q-Aggregation for CATE Model Selection—0
Hierarchical Model Selection for Graph Neural Netoworks—0
Hierarchical Proxy Modeling for Improved HPO in Time Series Forecasting—0
A Review of Fairness and A Practical Guide to Selecting Context-Appropriate Fairness Metrics in Machine Learning—0
High-Dimensional Dynamic Covariance Models with Random Forests—0
High-Dimensional Graphical Model Selection: Tractable Graph Families and Necessary Conditions—0
High-Dimensional Importance-Weighted Information Criteria: Theory and Optimality—0
Feedback-Controlled Sequential Lasso Screening—0
Causal Falling Rule Lists—0
Federated Model Search via Reinforcement Learning—0
High SNR Consistent Compressive Sensing—0
A Review of Cross-Sectional Matrix Exponential Spatial Models—0
Aggregation of Affine Estimators—0
Housing Price Prediction Model Selection Based on Lorenz and Concentration Curves: Empirical Evidence from Tehran Housing Market—0
How do some Bayesian Network machine learned graphs compare to causal knowledge?—0
A coupled-mechanisms modelling framework for neurodegeneration—0
Federated Learning with Correlated Data: Taming the Tail for Age-Optimal Industrial IoT—0
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