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Parikshit Gopalan
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Parikshit Gopalan is a researcher with Microsoft in Mountain View. He works with the Windows Azure storage team. Gopalan works on both theoretical and applied aspects of computer science. His theoretical work focuses primarily on coding theory, computational learning, pseudorandomness, Boolean function complexity, and the interplay among them. On the practical side, Gopalan is interested in erasure coding tailored to the needs of cloud data storage systems, which give good locality in addition to reliability.
Papers96 papers
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ITCS, (2020)
ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019), (2019): 15783-15793
neural information processing systems, (2019)
Bibtex
PVLDB, no. 11 (2019): 1442-1457
Lee Organick, Siena Dumas Ang, Yuan-Jyue Chen, Randolph Lopez,Sergey Yekhanin,Konstantin Makarychev,Miklos Z Racz,Govinda Kamath,Parikshit Gopalan,Bichlien Nguyen, Christopher N Takahashi, Sharon Newman
Nature biotechnology, no. 7 (2018): 660
arXiv: Learning, (2018)
ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 31 (NIPS 2018), (2018)
USENIX Annual Technical Conference, (2018): 387-400
ACM TRANSACTIONS ON ECONOMICS AND COMPUTATION, no. SP3-4 (2018)
Lee Organick, Siena Dumas Ang,Yuan-Jyue Chen, Randolph Lopez,Sergey Yekhanin,Konstantin Makarychev,Miklos Z Racz,Govinda Kamath,Parikshit Gopalan,Bichlien Nguyen, Christopher N Takahashi, Sharon Newman
Nature biotechnology, (2018)
SODA '17: Symposium on Discrete Algorithms
Barcelona
Spain
January, 2017, pp.2092-2108, (2017)
Cited by31EIBibtex
Douglas Carmean,Luis Ceze,Karin Strauss, Siena Dumas Ang,Robert Carlson, Yuan-Jyue Chen,Parikshit Gopalan,Gagan Gupta,Govinda Kamath, Randolph Lopez,Konstantin Makarychev, John Mulligan
Nature Biotechnology, (2017)
Cited by18Bibtex
SODA, (2017)
Electronic Colloquium on Computational Complexity, (2016): 59-70
Electronic Colloquium on Computational Complexity (ECCC), (2016)
(2015)
Cited by5Bibtex
(2015)
Cited by5Bibtex
Evolutionary Computation, no. 3-4 (2015)
2015 IEEE 56TH ANNUAL SYMPOSIUM ON FOUNDATIONS OF COMPUTER SCIENCE, (2015): 903-922
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