SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 426–450 of 2050 papers

TitleStatusHype
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
Show:102550
← PrevPage 18 of 82Next →

No leaderboard results yet.