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Scalable and Parallel Boosting with MapReduce
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1006/jcss.1997.1504openalex-snapshot
A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting
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NaradaBrokering: A Distributed Middleware Framework and Architecture for Enabling Durable Peer-to-Peer Grids
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Using Data Mining for Wine Quality Assessment
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Multi-resolution boosting for classification and regression problems
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Privacy-preserving boosting
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Identification of common molecular subsequences
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Improved Boosting Algorithms Using Confidence-rated Predictions
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Logistic Regression, AdaBoost and Bregman Distances
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Boosting Algorithms for Parallel and Distributed Learning
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BioGRID: a general repository for interaction datasets
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Introduction to Parallel Computing
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Database mining: a performance perspective
inferredcites →https://doi.org/10.1109/chinagrid.2009.39openalex-snapshot
MReC4.5: C4.5 Ensemble Classification with MapReduce
inferredcites →https://doi.org/10.1109/escience.2008.59openalex-snapshot
MapReduce for Data Intensive Scientific Analyses
inferredcites →https://doi.org/10.1142/s021848850200165xopenalex-snapshot
ACHIEVING k-ANONYMITY PRIVACY PROTECTION USING GENERALIZATION AND SUPPRESSION
inferredcites →https://doi.org/10.1145/1656274.1656278openalex-snapshot
The WEKA data mining software
inferredcites →https://doi.org/10.1145/279943.279960openalex-snapshot
Improved boosting algorithms using confidence-rated predictions
inferredcites →https://doi.org/10.1145/312129.312283openalex-snapshot
The application of AdaBoost for distributed, scalable and on-line learning
inferredcites →https://doi.org/10.1145/772862.772867openalex-snapshot
Tools for privacy preserving distributed data mining
inferredcites →https://doi.org/10.1145/773153.773174openalex-snapshot
Limiting privacy breaches in privacy preserving data mining
inferredcites →https://doi.org/10.1145/775047.775089openalex-snapshot
Transforming data to satisfy privacy constraints
inferredcites →https://doi.org/10.1145/974121.974131openalex-snapshot
State-of-the-art in privacy preserving data mining
inferredcites →https://doi.org/10.1214/aos/1016218223openalex-snapshot
Additive logistic regression: a statistical view of boosting (With discussion and a rejoinder by the authors)
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Popular Ensemble Methods: An Empirical Study
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Random forests
inferredcites →https://doi.org/10.5860/choice.42-0990openalex-snapshot
Introduction to parallel computing
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Multi-level Δ-learning for predicting the radiative decay rate constant of phosphorescent platinum( ii ) complexes
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