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dc.contributor.author
Liu, Ji
dc.contributor.author
Zhang, Ce
dc.date.accessioned
2020-09-09T13:20:59Z
dc.date.available
2020-07-22T02:52:09Z
dc.date.available
2020-09-08T15:57:52Z
dc.date.available
2020-09-09T13:20:59Z
dc.date.issued
2020-06-30
dc.identifier.isbn
978-1-68083-700-1
en_US
dc.identifier.isbn
978-1-68083-701-8
en_US
dc.identifier.issn
1931-7883
dc.identifier.issn
1931-7891
dc.identifier.other
10.1561/1900000062
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/427807
dc.description.abstract
Scalable and efficient distributed learning is one of the main driving forces behind the recent rapid advancement of machine learning and artificial intelligence. One prominent feature of this topic is that recent progress has been made by researchers in two communities: (1) the system community such as database, data management, and distributed systems, and (2) the machine learning and mathematical optimization community. The interaction and knowledge sharing between these two communities has led to the rapid development of new distributed learning systems and theory. In this monograph, we hope to provide a brief introduction of some distributed learning techniques that have recently been developed, namely lossy communication compression (e.g., quantization and sparsification), asynchronous communication, and decentralized communication. One special focus in this monograph is on making sure that it can be easily understood by researchers in both communities — on the system side, we rely on a simplified system model hiding many system details that are not necessary for the intuition behind the system speedups; while, on the theory side, we rely on minimal assumptions and significantly simplify the proof of some recent work to achieve comparable results. (© 2020 Copernicus GmbH)
en_US
dc.language.iso
en
en_US
dc.publisher
Now Publishers Inc.
en_US
dc.subject
Parallel and Distributed Database Systems
en_US
dc.subject
Optimization
en_US
dc.title
Distributed Learning Systems with First-Order Methods
en_US
dc.type
Monograph
dc.date.published
2020-06-24
ethz.journal.title
Foundations and Trends® in Databases
ethz.journal.volume
9
en_US
ethz.journal.issue
1
en_US
ethz.pages.start
1
en_US
ethz.pages.end
100
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Hanover, MA
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02150 - Dep. Informatik / Dep. of Computer Science::02663 - Institut für Computing Platforms / Institute for Computing Platforms::09588 - Zhang, Ce / Zhang, Ce
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02150 - Dep. Informatik / Dep. of Computer Science::02663 - Institut für Computing Platforms / Institute for Computing Platforms::09588 - Zhang, Ce / Zhang, Ce
ethz.date.deposited
2020-07-22T02:52:18Z
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2020-09-09T13:21:16Z
ethz.rosetta.lastUpdated
2021-02-15T17:06:19Z
ethz.rosetta.versionExported
true
ethz.COinS
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