Zobrazeno 1 - 10
of 88
pro vyhledávání: '"Atri, Rudra"'
Autor:
Kenneth Joseph, Huei-Yen Winnie Chen, Stefania Ionescu, Yuhao Du, Pranav Sankhe, Aniko Hannak, Atri Rudra
Publikováno v:
Applied Network Science, Vol 7, Iss 1, Pp 1-27 (2022)
Abstract We propose and extend a qualitative, complex systems methodology from cognitive engineering, known as the abstraction hierarchy, to model how potential interventions that could be carried out by social media platforms might impact social equ
Externí odkaz:
https://doaj.org/article/7a0caad6068242a2af6c8ad150bccea2
Autor:
Stacy A. Doore, Atri Rudra, Omowumi Ogunyemi, Trystan S. Goetze, Mehran Sahami, Thomas J. Cortina, Kiran Bhardwaj, Crystal Lee
Publikováno v:
Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 2.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::950ecd75878168663f631200d128c315
https://doi.org/10.1145/3545947.3569613
https://doi.org/10.1145/3545947.3569613
Publikováno v:
CSCW '20.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bde5413fcfc2d714e7211e7230ebedf0
https://doi.org/10.21428/93b2c832.2739b515
https://doi.org/10.21428/93b2c832.2739b515
Publikováno v:
PODS
In this paper, we prove topology dependent bounds on the number of rounds needed to compute Functional Aggregate Queries (FAQs) studied by Abo Khamis et al. [PODS 2016] in a synchronous distributed network under the model considered by Chattopadhyay
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3422acfcf52b58e2a9f90df83023198c
https://doi.org/10.1145/3294052.3319686
https://doi.org/10.1145/3294052.3319686
Publikováno v:
Proceedings of the ... Annual ACM-SIAM Symposium on Discrete Algorithms. ACM-SIAM Symposium on Discrete Algorithms. 2018
Matrix-vector multiplication is one of the most fundamental computing primitives. Given a matrix [Formula: see text] and a vector [Formula: see text] , it is known that in the worst case Θ(N(2)) operations over F are needed to compute Ab. Many types
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::8ef89bbe0a50318700f2e882b5fd9bd3
https://pubmed.ncbi.nlm.nih.gov/31130802
https://pubmed.ncbi.nlm.nih.gov/31130802
Fast linear transforms are ubiquitous in machine learning, including the discrete Fourier transform, discrete cosine transform, and other structured transformations such as convolutions. All of these transforms can be represented by dense matrix-vect
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ac606fa676837652d20910b7d05faefb
http://arxiv.org/abs/1903.05895
http://arxiv.org/abs/1903.05895
Publikováno v:
ACM Transactions on Database Systems. 41:1-45
We present a simple geometric framework for the relational join. Using this framework, we design an algorithm that achieves the fractional hypertree-width bound, which generalizes classical and recent worst-case algorithmic results on computing joins
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b7a91c9eb84de4cb0ac7f2db1ec7ffe0
https://doi.org/10.1145/2967101
https://doi.org/10.1145/2967101
Publikováno v:
STOC
Arikan's exciting discovery of polar codes has provided an altogether new way to efficiently achieve Shannon capacity. Given a (constant-sized) invertible matrix $M$, a family of polar codes can be associated with this matrix and its ability to appro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::abc8b85f0fb6e6a57233a620b984f94e
https://doi.org/10.1145/3188745.3188816
https://doi.org/10.1145/3188745.3188816