Active learning via collective inference in network regression problems
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Publication:2198209
DOI10.1016/j.ins.2018.05.028zbMath1440.68200OpenAlexW2809614429MaRDI QIDQ2198209
Donato Malerba, Annalisa Appice, Corrado Loglisci
Publication date: 9 September 2020
Published in: Information Sciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.ins.2018.05.028
Cites Work
- Unnamed Item
- Dealing with temporal and spatial correlations to classify outliers in geophysical data streams
- Multi-target support vector regression via correlation regressor chains
- Sample surveys: inference and analysis
- Selective sampling using the query by committee algorithm
- Sparse spatial autoregressions
- Summarizing numeric spatial data streams by trend cluster discovery
- Network regression with predictive clustering trees
- Active learning using transductive sparse Bayesian regression
- Using multiple time series analysis for geosensor data forecasting
- Leveraging temporal autocorrelation of historical data for improving accuracy in network regression
- NOTES ON CONTINUOUS STOCHASTIC PHENOMENA
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