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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 701–750 of 2050 papers

TitleStatusHype
mage based prognosis in head and neck cancer using convolutional neural networks: a case study in reproducibility and optimizationCode0
Random Matrix Analysis to Balance between Supervised and Unsupervised Learning under the Low Density Separation Assumption—0
GestureGPT: Toward Zero-Shot Free-Form Hand Gesture Understanding with Large Language Model AgentsCode0
Online Estimation with Rolling Validation: Adaptive Nonparametric Estimation with Streaming Data—0
VoxArabica: A Robust Dialect-Aware Arabic Speech Recognition System—0
Model Selection of Anomaly Detectors in the Absence of Labeled Validation Data—0
spateGAN: Spatio-Temporal Downscaling of Rainfall Fields Using a cGAN ApproachCode0
One For All & All For One: Bypassing Hyperparameter Tuning with Model Averaging For Cross-Lingual TransferCode0
IW-GAE: Importance Weighted Group Accuracy Estimation for Improved Calibration and Model Selection in Unsupervised Domain Adaptation—0
Target Variable Engineering—0
To token or not to token: A Comparative Study of Text Representations for Cross-Lingual TransferCode0
Risk Aware Benchmarking of Large Language Models—0
Transformers for Green Semantic Communication: Less Energy, More SemanticsCode0
On the Computational Complexity of Private High-dimensional Model SelectionCode0
Democratizing LLMs: An Exploration of Cost-Performance Trade-offs in Self-Refined Open-Source Models—0
SC-Safety: A Multi-round Open-ended Question Adversarial Safety Benchmark for Large Language Models in Chinese—0
Exploring the Maze of Multilingual Modeling—0
A Symmetry-based Framework for Model Selection of Coral Reef Population Growth Models—0
Combining UPerNet and ConvNeXt for Contrails Identification to reduce Global WarmingCode0
Test-Time Adaptation Induces Stronger Accuracy and Agreement-on-the-Line—0
Understanding prompt engineering may not require rethinking generalization—0
Driver Identification by an Ensemble of CNNs Obtained from Majority-Voting Model SelectionCode0
A ModelOps-based Framework for Intelligent Medical Knowledge Extraction—0
Tuning Large language model for End-to-end Speech Translation—0
LaPLACE: Probabilistic Local Model-Agnostic Causal ExplanationsCode0
Dynamic Interpretability for Model Comparison via Decision RulesCode0
Structural Risk Minimization for Learning Nonlinear Dynamics—0
Wave-shape Function Model Order Estimation by Trigonometric Regression—0
Pseudo Label Selection is a Decision Problem—0
Forecasting large collections of time series: feature-based methods—0
A closer look at parameter identifiability, model selection and handling of censored data with Bayesian Inference in mathematical models of tumour growth—0
Big model only for hard audios: Sample dependent Whisper model selection for efficient inferencesCode0
Improving VTE Identification through Adaptive NLP Model Selection and Clinical Expert Rule-based Classifier from Radiology Reports—0
A Convex Framework for Confounding Robust InferenceCode0
Estimating Stable Fixed Points and Langevin Potentials for Financial Dynamics—0
The Topology and Geometry of Neural RepresentationsCode0
Error Reduction from Stacked Regressions—0
DGM-DR: Domain Generalization with Mutual Information Regularized Diabetic Retinopathy ClassificationCode0
A Consistent and Scalable Algorithm for Best Subset Selection in Single Index Models—0
Granger Causal Inference in Multivariate Hawkes Processes by Minimum Message LengthCode0
A novel algebraic approach to time-reversible evolutionary modelsCode0
Parameter identifiability and model selection for partial differential equation models of cell invasionCode0
Generalized Information Criteria for Structured Sparse Models—0
AutoML-GPT: Large Language Model for AutoML—0
Subjectivity in Unsupervised Machine Learning Model Selection—0
SortedNet: A Scalable and Generalized Framework for Training Modular Deep Neural Networks—0
Exploring Model Transferability through the Lens of Potential EnergyCode0
Self-Supervision for Tackling Unsupervised Anomaly Detection: Pitfalls and Opportunities—0
Sparse Models for Machine Learning—0
Tryage: Real-time, intelligent Routing of User Prompts to Large Language Models—0
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