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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
Estimating the Number of Components in Finite Mixture Models via Variational Approximation—0
Automated Model Selection for Generalized Linear Models—0
On uncertainty-penalized Bayesian information criterion—0
Generalizing Machine Learning Evaluation through the Integration of Shannon Entropy and Rough Set Theory—0
A Sentiment Analysis of Medical Text Based on Deep Learning—0
A Realistic Protocol for Evaluation of Weakly Supervised Object LocalizationCode0
On the Necessity of Collaboration for Online Model Selection with Decentralized Data—0
Semantic Approach to Quantifying the Consistency of Diffusion Model Image GenerationCode0
Measuring Domain Shifts using Deep Learning Remote Photoplethysmography Model Similarity—0
The CAST package for training and assessment of spatial prediction models in RCode2
Idea23D: Collaborative LMM Agents Enable 3D Model Generation from Interleaved Multimodal InputsCode2
Dimension-free Relaxation Times of Informed MCMC Samplers on Discrete Spaces—0
Model Selection with Model Zoo via Graph LearningCode0
Predictive Analytics of Varieties of PotatoesCode0
GLEMOS: Benchmark for Instantaneous Graph Learning Model SelectionCode0
SpiKernel: A Kernel Size Exploration Methodology for Improving Accuracy of the Embedded Spiking Neural Network Systems—0
Learning the mechanisms of network growthCode0
Beyond One-Size-Fits-All: Multi-Domain, Multi-Task Framework for Embedding Model Selection—0
Individual Text Corpora Predict Openness, Interests, Knowledge and Level of Education—0
Bayesian Nonparametrics: An Alternative to Deep Learning—0
EL-MLFFs: Ensemble Learning of Machine Leaning Force Fields—0
Carbon Intensity-Aware Adaptive Inference of DNNs—0
An Experimental Study on the Rashomon Effect of Balancing Methods in Imbalanced ClassificationCode0
Conformal online model aggregationCode0
Bridge the Modality and Capability Gaps in Vision-Language Model Selection—0
On the Laplace Approximation as Model Selection Criterion for Gaussian Processes—0
DiTMoS: Delving into Diverse Tiny-Model Selection on MicrocontrollersCode0
Evaluating Large Language Models as Generative User Simulators for Conversational RecommendationCode0
Which LLM to Play? Convergence-Aware Online Model Selection with Time-Increasing Bandits—0
Detection of Unobserved Common Causes based on NML Code in Discrete, Mixed, and Continuous Variables—0
Pre-Trained Model Recommendation for Downstream Fine-tuning—0
Regularized DeepIV with Model Selection—0
A data-centric approach to class-specific bias in image data augmentation—0
Dendrogram of mixing measures: Hierarchical clustering and model selection for finite mixture models—0
Selection, Ensemble, and Adaptation: Advancing Multi-Source-Free Domain Adaptation via Architecture Zoo—0
A Unified Model Selection Technique for Spectral Clustering Based Motion Segmentation—0
Defining Expertise: Applications to Treatment Effect EstimationCode0
Unveiling the Potential of Robustness in Selecting Conditional Average Treatment Effect EstimatorsCode0
Z-AGI Labs at ClimateActivism 2024: Stance and Hate Event Detection on Social Media—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
Learning under Singularity: An Information Criterion improving WBIC and sBIC—0
Towards Versatile Graph Learning Approach: from the Perspective of Large Language Models—0
Benchmark Self-Evolving: A Multi-Agent Framework for Dynamic LLM EvaluationCode1
Modeling methodology for the accurate and prompt prediction of symptomatic events in chronic diseases—0
Confidence-aware Fine-tuning of Sequential Recommendation Systems via Conformal Prediction—0
Model Assessment and Selection under Temporal Distribution ShiftCode0
LoTa-Bench: Benchmarking Language-oriented Task Planners for Embodied AgentsCode2
Online Foundation Model Selection in Robotics—0
Local Projections Inference with High-Dimensional Covariates without Sparsity—0
Compressive Recovery of Signals Defined on Perturbed Graphs—0
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