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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.semanticscholar.org/paper/Consensus-based-distributed-linear-support-vector-Forero-Cano/802884ab11e81e978e53af5acd10d2fab8d61bef
This paper develops algorithms to train linear support vector machines (SVMs) when training data are distributed across different nodes and their communication to a centralized node is prohibited due to, for example, communication overhead or privacy reasons. To accomplish this goal, the centralized linear SVM problem is cast as the solution of coupled decentralized convex optimization ...
https://www.researchgate.net/publication/221284397_Consensus-based_distributed_linear_support_vector_machines
This paper develops algorithms to train linear support vector machines (SVMs) when training data are distributed across different nodes and their communication to a centralized node is prohibited ...
https://dl.acm.org/citation.cfm?doid=1791212.1791218
This paper develops algorithms to train linear support vector machines (SVMs) when training data are distributed across different nodes and their communication to a centralized node is prohibited due to, for example, communication overhead or privacy reasons.Cited by: 150
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://export.arxiv.org/pdf/1706.05039
nodes and tasks. We propose a consensus-based distributed transfer learning framework, where several tasks aim to find the best linear support vector machine (SVM) classifiers in a distributed network. With alternating direction method of multipliers, …
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.591.7247
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): This paper develops algorithms to train linear support vector machines (SVMs) when training data are distributed across different nodes and their communication to a centralized node is prohibited due to, for example, communication overhead or privacy reasons. To accomplish this goal, the centralized linear SVM …
https://ieeexplore.ieee.org/document/8362195/
Moreover, privacy can be violated as some tasks may contain sensitive and private data, which are communicated between nodes and tasks. We propose a consensus-based distributed transfer learning framework, where several tasks aim to find the best linear support vector machine (SVM) classifiers in a distributed network.Cited by: 2
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://dl.acm.org/citation.cfm?id=1859906
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
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