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Janardhan Kulkarni
Janardhan Kulkarni
Microsoft Research, Redmond
Verified email at cs.washington.edu
Title
Cited by
Cited by
Year
Collecting telemetry data privately
B Ding, J Kulkarni, S Yekhanin
Advances in Neural Information Processing Systems 30, 2017
8852017
Projector: Agile reconfigurable data center interconnect
M Ghobadi, R Mahajan, A Phanishayee, N Devanur, J Kulkarni, ...
Proceedings of the 2016 ACM SIGCOMM Conference, 216-229, 2016
3852016
Differentially private fine-tuning of language models
D Yu, S Naik, A Backurs, S Gopi, HA Inan, G Kamath, J Kulkarni, YT Lee, ...
arXiv preprint arXiv:2110.06500, 2021
3492021
Morpheus: Towards automated {SLOs} for enterprise clusters
SA Jyothi, C Curino, I Menache, SM Narayanamurthy, A Tumanov, ...
12th USENIX symposium on operating systems design and implementation (OSDI …, 2016
3422016
{GRAPHENE}: Packing and {Dependency-Aware} scheduling for {Data-Parallel} clusters
R Grandl, S Kandula, S Rao, A Akella, J Kulkarni
12th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2016
2812016
Competitive algorithms from competitive equilibria: Non-clairvoyant scheduling under polyhedral constraints
S Im, J Kulkarni, K Munagala
Journal of the ACM (JACM) 65 (1), 1-33, 2017
842017
Looking beyond {GPUs} for {DNN} scheduling on {Multi-Tenant} clusters
J Mohan, A Phanishayee, J Kulkarni, V Chidambaram
16th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2022
752022
When does differentially private learning not suffer in high dimensions?
X Li, D Liu, TB Hashimoto, HA Inan, J Kulkarni, YT Lee, A Guha Thakurta
Advances in Neural Information Processing Systems 35, 28616-28630, 2022
592022
Selfishmigrate: A scalable algorithm for non-clairvoyantly scheduling heterogeneous processors
S Im, J Kulkarni, K Munagala, K Pruhs
2014 IEEE 55th Annual Symposium on Foundations of Computer Science, 531-540, 2014
582014
Accuracy, interpretability, and differential privacy via explainable boosting
H Nori, R Caruana, Z Bu, JH Shen, J Kulkarni
International conference on machine learning, 8227-8237, 2021
522021
Deterministically Maintaining a (2 + )-Approximate Minimum Vertex Cover in O(1/2) Amortized Update Time
S Bhattacharya, J Kulkarni
Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete …, 2019
512019
Locally private gaussian estimation
M Joseph, J Kulkarni, J Mao, SZ Wu
Advances in Neural Information Processing Systems 32, 2019
492019
Privacy-preserving in-context learning with differentially private few-shot generation
X Tang, R Shin, HA Inan, A Manoel, F Mireshghallah, Z Lin, S Gopi, ...
arXiv preprint arXiv:2309.11765, 2023
482023
Exploring the limits of differentially private deep learning with group-wise clipping
J He, X Li, D Yu, H Zhang, J Kulkarni, YT Lee, A Backurs, N Yu, J Bian
arXiv preprint arXiv:2212.01539, 2022
472022
Hardware protection for differential privacy
JD Benaloh, JD KULKARNI, JS ALLEN, JR Lorch, ME CHASE, ...
US Patent 10,977,384, 2021
472021
An algorithmic framework for differentially private data analysis on trusted processors
J Allen, B Ding, J Kulkarni, H Nori, O Ohrimenko, S Yekhanin
Advances in Neural Information Processing Systems 32, 2019
462019
Fast and memory efficient differentially private-sgd via jl projections
Z Bu, S Gopi, J Kulkarni, YT Lee, H Shen, U Tantipongpipat
Advances in Neural Information Processing Systems 34, 19680-19691, 2021
452021
Differentially private release of synthetic graphs
M Eliáš, M Kapralov, J Kulkarni, YT Lee
Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete …, 2020
422020
Tinygsm: achieving> 80% on gsm8k with small language models
B Liu, S Bubeck, R Eldan, J Kulkarni, Y Li, A Nguyen, R Ward, Y Zhang
arXiv preprint arXiv:2312.09241, 2023
412023
Differentially private set union
S Gopi, P Gulhane, J Kulkarni, JH Shen, M Shokouhi, S Yekhanin
International Conference on Machine Learning, 3627-3636, 2020
412020
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Articles 1–20