Nihar B. Shah

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Kannan RamchandranProfessor of Electrical Engineering and Computer Science, UC BerkeleyVerifierad e-postadress på eecs.berkeley.edu
K. V. Rashmi (Rashmi Vinayak)Associate Professor, CS, Carnegie Mellon UniversityVerifierad e-postadress på cs.cmu.edu
P Vijay KumarHon. Professor, Indian Institute of ScienceVerifierad e-postadress på iisc.ac.in
Martin WainwrightProfessor, EECS/Mathematics, Massachusetts Institute of TechnologyVerifierad e-postadress på mit.edu
Ivan StelmakhCarnegie Mellon UniversityVerifierad e-postadress på cs.cmu.edu
Sivaraman BalakrishnanCarnegie Mellon UniversityVerifierad e-postadress på stat.cmu.edu
Aarti SinghProfessor of Machine Learning Department, Carnegie Mellon UniversityVerifierad e-postadress på cmu.edu
Abhay Parekh(Ex) Adjunct Professor, Electrical Engineering and Computer Science, U C BerkeleyVerifierad e-postadress på eecs.berkeley.edu
Jingyan WangToyota Technological Institute at ChicagoVerifierad e-postadress på ttic.edu
Denny ZhouResearch Scientist, Google DeepMindVerifierad e-postadress på google.com
Steven JecmenCarnegie Mellon UniversityVerifierad e-postadress på cs.cmu.edu
Kangwook LeeUniversity of Wisconsin-MadisonVerifierad e-postadress på wisc.edu
Charvi RastogiGoogle DeepMindVerifierad e-postadress på google.com
Fei FangCarnegie Mellon UniversityVerifierad e-postadress på cmu.edu
Ryan LiuPhD Student in Computer Science, Princeton UniversityVerifierad e-postadress på princeton.edu
Hal Daumé IIIAssociate Professor of Computer Science, University of MarylandVerifierad e-postadress på umiacs.umd.edu
Isabelle GuyonDirector of Research, Google; Prof. UPSaclay; President ChaLearnVerifierad e-postadress på chalearn.org
Dhruba BorthakurHDFS, RocksDB, RocksetVerifierad e-postadress på rockset.com
Vincent ConitzerProfessor of CS, Carnegie Mellon University; Professor of CS and Philosophy, University of OxfordVerifierad e-postadress på cs.cmu.edu
Preetum NakkiranApple ML ResearchVerifierad e-postadress på cs.harvard.edu

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Nihar B. Shah

ML and CS departments, Carnegie Mellon University

Verifierad e-postadress på cs.cmu.edu - Startsida

machine learning statistics social choice peer review


Titel Sortera efter citat Sortera efter år Sortera efter titel	Citeras av Citeras av	År
Optimal Exact-Regenerating Codes for Distributed Storage at the MSR and MBR Points via a Product-Matrix Construction KV Rashmi, NB Shah, PV Kumar (* = equal contribution) Information Theory, IEEE Transactions on 57 (8), 5227-5239, 2011	891	2011
A Solution to the Network Challenges of Data Recovery in Erasure-coded Distributed Storage Systems: A Study on the Facebook Warehouse Cluster KV Rashmi, NB Shah, D Gu, H Kuang, D Borthakur, K Ramchandran USENIX HotStorage 2013, 2013	381	2013
Explicit construction of optimal exact regenerating codes for distributed storage KV Rashmi, NB Shah, PV Kumar, ... Communication, Control, and Computing, 2009. Allerton 2009. 47th Annual …, 2009	340	2009
Distributed storage codes with repair-by-transfer and nonachievability of interior points on the storage-bandwidth tradeoff NB Shah, KV Rashmi, PV Kumar, ... Information Theory, IEEE Transactions on 58 (3), 1837-1852, 2012	316	2012
A" hitchhiker's" guide to fast and efficient data reconstruction in erasure-coded data centers KV Rashmi, NB Shah, D Gu, H Kuang, D Borthakur, K Ramchandran Proceedings of the 2014 ACM conference on SIGCOMM, 331-342, 2014	307	2014
When Do Redundant Requests Reduce Latency? NB Shah, K Lee, K Ramchandran 51st Allerton Conference on Communication, Control, and Computing, 2013	256	2013
Interference alignment in regenerating codes for distributed storage: Necessity and code constructions NB Shah, KV Rashmi, PV Kumar, ... Information Theory, IEEE Transactions on 58 (4), 2134-2158, 2012	255	2012
Simple, robust and optimal ranking from pairwise comparisons NB Shah, MJ Wainwright Journal of machine learning research 18 (199), 1-38, 2018	231	2018
One extra bit of download ensures perfectly private information retrieval NB Shah, KV Rashmi, K Ramchandran 2014 IEEE International Symposium on Information Theory, 856-860, 2014	231	2014
Estimation from Pairwise Comparisons: Sharp Minimax Bounds with Topology Dependence NB Shah, S Balakrishnan, J Bradley, A Parekh, K Ramchandran, ... Proceedings of the Eighteenth International Conference on Artificial …, 2015	228*	2015
Stochastically transitive models for pairwise comparisons: Statistical and computational issues N Shah, S Balakrishnan, A Guntuboyina, M Wainwright IEEE Transactions on Information Theory, 2017	191	2017
Having your cake and eating it too: Jointly optimal erasure codes for {I/O}, storage, and network-bandwidth KV Rashmi, P Nakkiran, J Wang, NB Shah, K Ramchandran 13th USENIX Conference on File and Storage Technologies (FAST 15), 81-94, 2015	178	2015
The MDS queue: Analysing the latency performance of erasure codes K Lee, NB Shah, L Huang, K Ramchandran IEEE Transactions on Information Theory 63 (5), 2822-2842, 2017	176*	2017
Active ranking from pairwise comparisons and when parametric assumptions do not help R Heckel, NB Shah, K Ramchandran, MJ Wainwright	147	2019
Challenges, experiments, and computational solutions in peer review NB Shah Communications of the ACM 65 (6), 76-87, 2022	144*	2022
Information-theoretically Secure Regenerating Codes for Distributed Storage NB Shah, KV Rashmi, PV Kumar (* = equal contribution) IEEE Globecom 2011, 2011	140	2011
A piggybacking design framework for read-and download-efficient distributed storage codes KV Rashmi, NB Shah, K Ramchandran IEEE Transactions on Information Theory 63 (9), 5802-5820, 2017	133	2017
Double or nothing: Multiplicative incentive mechanisms for crowdsourcing NB Shah, D Zhou Journal of Machine Learning Research 17 (165), 1-52, 2016	128	2016
A case for ordinal peer-evaluation in MOOCs NB Shah, JK Bradley, A Parekh, M Wainwright, K Ramchandran NIPS workshop on data driven education 15, 67, 2013	128	2013
Overcoming calibration problems in pattern labeling with pairwise ratings: application to personality traits B Chen, S Escalera, I Guyon, V Ponce-López, N Shah, M Oliu Simón European Conference on Computer Vision, 419-432, 2016	127	2016

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