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Found 13 papers, 4 papers with code
PeaTMOSS: A Dataset and Initial Analysis of Pre-Trained Models in Open-Source Software
Our analysis of this dataset provides the first summary statistics for the PTM supply chain, showing the trend of PTM development and common shortcomings of PTM package documentation.
PeaTMOSS: Mining Pre-Trained Models in Open-Source Software
Developing and training deep learning models is expensive, so software engineers have begun to reuse pre-trained deep learning models (PTMs) and fine-tune them for downstream tasks.
Naming Practices of Pre-Trained Models in Hugging Face
PTM authors should choose appropriate names for their PTMs, which would facilitate model discovery and reuse.
Analysis of Failures and Risks in Deep Learning Model Converters: A Case Study in the ONNX Ecosystem
We find that the node conversion stage of a model converter accounts for ~75% of the defects and 33% of reported failure are related to semantically incorrect models.
Challenges and Practices of Deep Learning Model Reengineering: A Case Study on Computer Vision
We describe this process as deep learning model reengineering.
An Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registry
We interviewed 12 practitioners from the most popular PTM ecosystem, Hugging Face, to learn the practices and challenges of PTM reuse.
Discrepancies among Pre-trained Deep Neural Networks: A New Threat to Model Zoo Reliability
Among the top 10 discrepancies, we find differences of 1. 23%-2. 62% in accuracy and 9%-131% in latency.
A Note on Comparison of F-measures
We comment on a recent TKDE paper "Linear Approximation of F-measure for the Performance Evaluation of Classification Algorithms on Imbalanced Data Sets", and make two improvements related to comparison of F-measures for two prediction rules.
An Experience Report on Machine Learning Reproducibility: Guidance for Practitioners and TensorFlow Model Garden Contributors
To promote best practices within the engineering community, academic institutions and Google have partnered to launch a Special Interest Group on Machine Learning Models (SIGMODELS) whose goal is to develop exemplary implementations of prominent machine learning models in community locations such as the TensorFlow Model Garden (TFMG).
Statistical Formulas for F Measures
We provide analytic formulas for the standard error and confidence intervals for the F measures, based on a property of asymptotic normality in the large sample limit.
Multi-sense Definition Modeling using Word Sense Decompositions
Word embeddings capture syntactic and semantic information about words.
Combining Random Walks and Nonparametric Bayesian Topic Model for Community Detection
Community detection has been an active research area for decades.
Hierarchical Mixtures-of-Experts for Exponential Family Regression Models with Generalized Linear Mean Functions: A Survey of Approximation and Consistency Results
We investigate a class of hierarchical mixtures-of-experts (HME) models where exponential family regression models with generalized linear mean functions of the form psi(ga+fx^Tfgb) are mixed.
