Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Tharindu Adikari"'
Autor:
Stark C. Draper, Tharindu Adikari
Publikováno v:
IEEE Journal on Selected Areas in Information Theory. 2:970-986
An increasing bottleneck in decentralized optimization is communication. Bigger models and growing datasets mean that decentralization of computation is important and that the amount of information exchanged is quickly growing. While compression tech
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::63144684cb7e1f323c593e7691e3d18b
https://doi.org/10.1109/jsait.2021.3103494
https://doi.org/10.1109/jsait.2021.3103494
Publikováno v:
ICASSP
Elasticity is offered by cloud service providers to exploit under-utilized computing resources. The low-cost elastic nodes can leave and join any time during the computation cycle. The possibility of elastic events occurring together with the problem
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7baf2fa09b7d4d3b3894deb2cc01c87e
Autor:
Stark C. Draper, Tharindu Adikari
Publikováno v:
ISTC
Distributed optimization has become the norm for training machine learning models on large datasets. Learning bigger models on such systems leads to the exchange of large-volume updates. For this reason, limits on network communication in a distribut
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d5753146bbe9363c8dbb4f0fa3266614
https://doi.org/10.1109/istc49272.2021.9594251
https://doi.org/10.1109/istc49272.2021.9594251
Autor:
Stark C. Draper, Tharindu Adikari
Publikováno v:
ICASSP
We consider decentralized consensus optimization when workers sample data from non-identical distributions and perform variable amounts of work due to slow nodes known as stragglers. The problem of non-identical distributions and the problem of varia
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::77f997f0aa050cf0bd7da8c6470f9384
https://doi.org/10.1109/icassp40776.2020.9053329
https://doi.org/10.1109/icassp40776.2020.9053329
Autor:
Stark C. Draper, Tharindu Adikari
Publikováno v:
CISS
We introduce a semiparametric approach to neighbor-based classification. We build off the recently proposed Boundary Trees algorithm by Mathy et al.(2015) which enables fast neighbor-based classification, regression and retrieval in large datasets. W
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a2baf0d3159be36053329a4c751b2138
http://arxiv.org/abs/1810.11165
http://arxiv.org/abs/1810.11165