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https://www.dtc.umn.edu/s/resources/jmlr2010.pdf
CONSENSUS-BASED DISTRIBUTED SUPPORT VECTOR MACHINES to a classifier trained using the data of nodes that remain operational. But ev en if the net-work becomes disconnected, the proposed algorithm will stay operational with performance
https://www.researchgate.net/publication/220321057_Consensus-Based_Distributed_Support_Vector_Machines
Consensus-Based Distributed Support Vector Machines Article (PDF Available) in Journal of Machine Learning Research 11:1663-1707 · May 2010 with 267 Reads How we measure 'reads'
https://experts.umn.edu/en/publications/consensus-based-distributed-support-vector-machines
abstract = "This paper develops algorithms to train support vector machines when training data are distributed across different nodes, and their communication to a centralized processing unit is prohibited due to, for example, communication complexity, scalability, or privacy reasons.Cited by: 366
https://www.researchgate.net/publication/221284397_Consensus-based_distributed_linear_support_vector_machines
Consensus-based distributed linear support vector machines ... proposed a distributed learning method for linear SVMs based on a consensus of weights and biases between single-hop neighboring ...
https://www.semanticscholar.org/paper/Consensus-based-distributed-linear-support-vector-Forero-Cano/802884ab11e81e978e53af5acd10d2fab8d61bef
@inproceedings{Forero2010ConsensusbasedDL, title={Consensus-based distributed linear support vector machines}, author={Pedro A. Forero and Alfonso Cano and Georgios B. Giannakis}, booktitle={IPSN '10}, year={2010} } Pedro A. Forero, Alfonso Cano, Georgios B. Giannakis This paper develops algorithms ...
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.407.6366
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): This paper develops algorithms to train support vector machines when training data are distributed across different nodes, and their communication to a centralized processing unit is prohibited due to, for example, communication complexity, scalability, or privacy reasons.
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