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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,657 papers · 148 categories

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3 results for “data-copying”

A Non-Parametric Test to Detect Data-Copying in Generative Modelscs.LG

New test detects when generative models memorize training data.

problem Detecting when generative models overfit by memorizing training data.

method A non-parametric three-sample test using training set, target distribution, and model-generated samples.

result The test effectively detects data-copying in various models and datasets.

generative models data-copying overfitting non-parametric test machine learning

2020-04-12abs ↗pdf ↗

Data Plagiarism Index: Characterizing the Privacy Risk of Data-Copying in Tabular Generative Modelscs.LG

This paper introduces DPI, a new metric to assess data-copying risk in tabular data.

problem Measuring privacy risk of data-copying in tabular generative models.

method Proposes Data Plagiarism Index (DPI) for evaluating data-copying risk.

result DPI identifies data-copying threats to tabular data models, highlighting privacy and fairness issues.

Data Plagiarism Index Membership Inference Attack Tabular Generative Models Privacy Risk Data Copying

2024-06-18abs ↗pdf ↗

On gradient descent training under data augmentation with on-line noisy copiesstat.ML

Paper analyzes gradient descent with noisy data copies for linear regression, showing regularization and acceleration effects.

problem Improving generalization in machine learning through data augmentation with noise.

method Gradient descent with on-line noisy copies for linear regression analysis.

result Training with on-line noisy copies is equivalent to ridge regularization with a specific regularization parameter.

gradient descent data augmentation noisy copies ridge regularization acceleration

2022-06-08abs ↗pdf ↗