Proposes applying social choice theory as a modeling language and axiomatic tool for incorporating collective input across the ML development pipeline.
The Effects of Data Quality on Machine Learning Performance on Tabular Data.Inf
3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
LADSG is a unified defense framework that reduces success rates of passive, active, and direct label inference attacks in VFL by 30-60% via label anonymization, gradient substitution, and norm-based filtering.
Rule-based model selection in time series forecasting achieves low accuracy and exhibits high ranking instability across data regimes and forecasting horizons.
citing papers explorer
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AI of the People, by the People, for the People: A Social Choice Approach to Collective Control of Artificial Intelligence
Proposes applying social choice theory as a modeling language and axiomatic tool for incorporating collective input across the ML development pipeline.
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LADSG: Label-Anonymized Distillation and Similar Gradient Substitution for Label Privacy in Vertical Federated Learning
LADSG is a unified defense framework that reduces success rates of passive, active, and direct label inference attacks in VFL by 30-60% via label anonymization, gradient substitution, and norm-based filtering.
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Why Model Selection Fails in Time Series Forecasting: An Empirical Study of Instability Across Data Regimes
Rule-based model selection in time series forecasting achieves low accuracy and exhibits high ranking instability across data regimes and forecasting horizons.