sudip roy
sudip roy
Потвърден имейл адрес: google.com - Начална страница
Tfx: A tensorflow-based production-scale machine learning platform
D Baylor, E Breck, HT Cheng, N Fiedel, CY Foo, Z Haque, S Haykal, ...
Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017
Data validation for machine learning
N Polyzotis, M Zinkevich, S Roy, E Breck, S Whang
Proceedings of machine learning and systems 1, 334-347, 2019
Data management challenges in production machine learning
N Polyzotis, S Roy, SE Whang, M Zinkevich
Proceedings of the 2017 ACM International Conference on Management of Data …, 2017
Goods: Organizing google's datasets
A Halevy, F Korn, NF Noy, C Olston, N Polyzotis, S Roy, SE Whang
Proceedings of the 2016 International Conference on Management of Data, 795-806, 2016
Data lifecycle challenges in production machine learning: a survey
N Polyzotis, S Roy, SE Whang, M Zinkevich
ACM SIGMOD Record 47 (2), 17-28, 2018
Performance anomaly diagnosis
AC Konig, I Dvorkin, M Kumar, S Roy
US Patent 9,904,584, 2018
Pathways: Asynchronous distributed dataflow for ml
P Barham, A Chowdhery, J Dean, S Ghemawat, S Hand, D Hurt, M Isard, ...
Proceedings of Machine Learning and Systems 4, 430-449, 2022
Managing Google's data lake: an overview of the Goods system.
AY Halevy, F Korn, NF Noy, C Olston, N Polyzotis, S Roy, SE Whang
IEEE Data Eng. Bull. 39 (3), 5-14, 2016
The Homeostasis Protocol: Avoiding Transaction Coordination Through Program Analysis
S Roy, L Kot, G Bender, B Ding, H Hojjat, C Koch, N Foster, J Gehrke
SIGMOD, 2015
PerfAugur: Robust Diagnostics for Performance Anomalies in Cloud Services
S Roy, C Konig, I Dvorkin, M Kumar
International Conference on Data Engineering, 2015
A learned performance model for tensor processing units
S Kaufman, P Phothilimthana, Y Zhou, C Mendis, S Roy, A Sabne, ...
Proceedings of Machine Learning and Systems 3, 387-400, 2021
Equality saturation for tensor graph superoptimization
Y Yang, P Phothilimthana, Y Wang, M Willsey, S Roy, J Pienaar
Proceedings of Machine Learning and Systems 3, 255-268, 2021
Transferable graph optimizers for ml compilers
Y Zhou, S Roy, A Abdolrashidi, D Wong, P Ma, Q Xu, H Liu, ...
Advances in Neural Information Processing Systems 33, 13844-13855, 2020
Gdp: Generalized device placement for dataflow graphs
Y Zhou, S Roy, A Abdolrashidi, D Wong, PC Ma, Q Xu, M Zhong, H Liu, ...
arXiv preprint arXiv:1910.01578, 2019
Tensorflow data validation: Data analysis and validation in continuous ml pipelines
E Caveness, PS GC, Z Peng, N Polyzotis, S Roy, M Zinkevich
Proceedings of the 2020 ACM SIGMOD International Conference on Management of …, 2020
A flexible approach to autotuning multi-pass machine learning compilers
PM Phothilimthana, A Sabne, N Sarda, KS Murthy, Y Zhou, ...
2021 30th International Conference on Parallel Architectures and Compilation …, 2021
Quantum Databases
S Roy, L Kot, C Koch
CIDR, 2013
Entangled queries: enabling declarative data-driven coordination
N Gupta, L Kot, S Roy, G Bender, J Gehrke, C Koch
Proceedings of the 2011 international conference on Management of data, 673-684, 2011
A layout-aware physical design method for constructing feasible QCA circuits
M Bubna, S Roy, N Shenoy, S Mazumdar
Proceedings of the 18th ACM Great Lakes symposium on VLSI, 243-248, 2008
Beyond isolation: Research opportunities in declarative data-driven coordination
L Kot, N Gupta, S Roy, J Gehrke, C Koch
ACM SIGMOD Record 39 (1), 27-32, 2010
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