Zobrazeno 1 - 10
of 58
pro vyhledávání: '"Mert Pilanci"'
Autor:
Burak Bartan, Mert Pilanci
Publikováno v:
IEEE Transactions on Information Theory. 69:3850-3879
We consider distributed optimization methods for problems where forming the Hessian is computationally challenging and communication is a significant bottleneck. We leverage randomized sketches for reducing the problem dimensions as well as preservin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f135488feafcd826bb1fe03ce20a7eb5
https://doi.org/10.1109/tit.2023.3247559
https://doi.org/10.1109/tit.2023.3247559
Autor:
Burak Bartan, Mert Pilanci
Publikováno v:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::57d8b82b1b16cd6a9093006741b10a6a
https://doi.org/10.1109/icassp49357.2023.10095613
https://doi.org/10.1109/icassp49357.2023.10095613
Publikováno v:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4997b00bb242bcdd562c1fa62819fc62
https://doi.org/10.1109/icassp49357.2023.10095529
https://doi.org/10.1109/icassp49357.2023.10095529
Publikováno v:
IEEE Journal on Selected Areas in Information Theory. 3:183-196
We study first-order optimization algorithms under the constraint that the descent direction is quantized using a pre-specified budget of $R$-bits per dimension, where $R \in (0 ,\infty)$. We propose computationally efficient optimization algorithms
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ba5a7089c2c0b0b75f5ddf113af399b7
https://doi.org/10.1109/jsait.2022.3198412
https://doi.org/10.1109/jsait.2022.3198412
Autor:
Mert Pilanci
Publikováno v:
IEEE Transactions on Information Theory. 68:2211-2238
We introduce an error resilient distributed computing method based on an extension of the channel polarization phenomenon to distributed algorithms. The method leverages an algorithmic split operation that transforms two identical compute nodes to sl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4cf10e5717a9dd0f29380851c0bf6798
https://doi.org/10.1109/tit.2021.3139009
https://doi.org/10.1109/tit.2021.3139009
Publikováno v:
IEEE Signal Processing Letters. 29:26-30
The ever-increasing need for real-time 3D perception for autonomy has resulted in development of a new generation of high-resolution perception sensors paired with powerful edge processors and advanced perception algorithms. However, processing of th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::36fc5a4631841cc89801b2d20aa33213
https://doi.org/10.1109/lsp.2021.3122355
https://doi.org/10.1109/lsp.2021.3122355
Publikováno v:
2022 5th International Conference on Signal Processing and Machine Learning.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2e7d4fd694b183613e744282e374ed25
https://doi.org/10.1145/3556384.3556414
https://doi.org/10.1145/3556384.3556414
A cumbersome operation in many scientific fields, is inverting large full-rank matrices. In this paper, we propose a coded computing approach for recovering matrix inverse approximations. We first present an approximate matrix inversion algorithm whi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0e3ece52b5c09be970a6ea6f5818aeb0
http://arxiv.org/abs/2207.06271
http://arxiv.org/abs/2207.06271
Publikováno v:
IEEE Journal on Selected Areas in Information Theory. 1:660-668
In this work, we consider the deterministic optimization using random projections as a statistical estimation problem, where the squared distance between the predictions from the estimator and the true solution is the error metric. In approximately s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7d693d07f15dc5edbcb035a7cb78e184
https://doi.org/10.1109/jsait.2020.3039509
https://doi.org/10.1109/jsait.2020.3039509
Autor:
Beliz Gunel, Arda Sahiner, Arjun D. Desai, Akshay S. Chaudhari, Shreyas Vasanawala, Mert Pilanci, John Pauly
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031164453
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4441b207448af37bcdfc75b7563d241e
https://doi.org/10.1007/978-3-031-16446-0_70
https://doi.org/10.1007/978-3-031-16446-0_70