Govinda M. Kamath
Govinda M. Kamath
Microsoft Research New England Lab, Cambridge, MA, USA
Verified email at microsoft.com - Homepage
Title
Cited by
Cited by
Year
Optimal Linear Codes with a Local-Error-Correction Property
N Prakash, GM Kamath, V Lalitha, PV Kumar
Information Theory Proceedings (ISIT), 2012 IEEE International Symposium on …, 2012
1962012
Random access in large-scale DNA data storage
L Organick, SD Ang, YJ Chen, R Lopez, S Yekhanin, K Makarychev, ...
Nature biotechnology 36 (3), 242, 2018
1882018
Codes with local regeneration and erasure correction
GM Kamath, N Prakash, V Lalitha, PV Kumar
IEEE Transactions on Information Theory 60 (8), 4637-4660, 2014
1372014
Fast and accurate single-cell RNA-Seq analysis by clustering of transcript-compatibility counts
V Ntranos, GM Kamath, J Zhang, L Pachter, D Tse
Genome Biology 17 (112), 2016
972016
Codes with local regeneration
GM Kamath, N Prakash, V Lalitha, PV Kumar
Information Theory Proceedings (ISIT), 2013 IEEE International Symposium on …, 2013
812013
HINGE: Long-Read Assembly Achieves Optimal Repeat Resolution
GM Kamath, I Shomorony, F Xia, TA Courtade, DN Tse
Genome Research 27 (May 2017), 747-756, 2017
762017
Explicit MBR all-symbol locality codes
GM Kamath, N Silberstein, N Prakash, AS Rawat, V Lalitha, OO Koyluoglu, ...
Information Theory Proceedings (ISIT), 2013 IEEE International Symposium on …, 2013
552013
Community recovery in graphs with locality
Y Chen, GM Kamath, C Suh, DN Tse
International Conference on Machine Learning, 2016
252016
Scaling up DNA data storage and random access retrieval
L Organick, SD Ang, YJ Chen, R Lopez, S Yekhanin, K Makarychev, ...
bioRxiv, 114553, 2017
182017
Valid post-clustering differential analysis for single-cell RNA-Seq
JM Zhang, GM Kamath, DN Tse
Cell systems 9.4, 2019
13*2019
Medoids in almost linear time via multi-armed bandits
V Bagaria, GM Kamath, V Ntranos, MJ Zhang, DN Tse
Proceedings of the Twenty-First International Conference on Artificial …, 2018
132018
Adaptive monte-carlo optimization
V Bagaria, GM Kamath, DN Tse
arXiv preprint arXiv:1805.08321, 2018
112018
Optimal haplotype assembly from high-throughput mate-pair reads
GM Kamath, E Şaşoğlu, DN Tse
2015 IEEE International Symposium on Information Theory (ISIT), 914-918, 2015
102015
Partial DNA assembly: a rate-distortion perspective
I Shomorony, GM Kamath, F Xia, TA Courtade, DN Tse
Information Theory (ISIT), 2016 IEEE International Symposium on, 1799-1803, 2016
62016
Regenerating Codes: a Reformulated Storage-Bandwidth Trade-off and a New Construction
GM Kamath, PV Kumar
National Conference on Communication 2012, 1-5, 2012
32012
Spectral Jaccard Similarity: A new approach to estimating pairwise sequence alignments
T Baharav, GM Kamath, DN Tse, I Shomorony
Cell Patterns 1 (6), 2020
12020
Proof-of-Stake Longest Chain Protocols Revisited
X Wang, GM Kamath, V Bagaria, S Kannan, S Oh, D Tse, P Viswanath
arXiv preprint arXiv:1910.02218, 2019
12019
Adaptive Learning of Rank-One Models for Efficient Pairwise Sequence Alignment
GM Kamath, T Baharav, I Shomorony
Advances in Neural Information Processing Systems 33, 2020
2020
crispr2vec: Machine Learning Model Predicts Off-Target Cuts of CRISPR systems
TB Trivedi, R Boger, GM Kamath, G Evangelopoulos, J Cate, J Doudna, ...
bioRxiv, 2020
2020
Almost Linear Time Algorithms for Problems of Computational Genomics
GM Kamath
Stanford University, 2019
2019
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Articles 1–20