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Janardhan Kulkarni
Janardhan Kulkarni
Microsoft Research, Redmond
Bestätigte E-Mail-Adresse bei cs.washington.edu
Titel
Zitiert von
Zitiert von
Jahr
Collecting telemetry data privately
B Ding, J Kulkarni, S Yekhanin
Advances in Neural Information Processing Systems 30, 2017
5752017
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
3092016
Morpheus: Towards Automated SLOs for Enterprise Clusters.
SA Jyothi, C Curino, I Menache, SM Narayanamurthy, A Tumanov, ...
OSDI, 117-134, 2016
2822016
G: Packing and dependency-aware scheduling for data-parallel clusters
R Grandl, S Kandula, S Rao, A Akella, J Kulkarni
Proceedings of OSDI16: 12th USENIX Symposium on Operating Systems Design and …, 2016
2262016
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
792021
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
712017
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
532014
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
382019
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
382019
Tight bounds for online vector scheduling
S Im, N Kell, J Kulkarni, D Panigrahi
2015 IEEE 56th Annual Symposium on Foundations of Computer Science, 525-544, 2015
352015
Locally private gaussian estimation
M Joseph, J Kulkarni, J Mao, SZ Wu
Advances in Neural Information Processing Systems 32, 2019
342019
Robust price of anarchy bounds via LP and fenchel duality
J Kulkarni, V Mirrokni
Proceedings of the twenty-sixth annual ACM-SIAM symposium on Discrete …, 2014
302014
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
292021
Differentially private set union
S Gopi, P Gulhane, J Kulkarni, JH Shen, M Shokouhi, S Yekhanin
International Conference on Machine Learning, 3627-3636, 2020
242020
Parallel batch-dynamic graphs: Algorithms and lower bounds
L Dhulipala, D Durfee, J Kulkarni, R Peng, S Sawlani, X Sun
Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete …, 2020
242020
Coordination mechanisms from (almost) all scheduling policies
S Bhattacharya, S Im, J Kulkarni, K Munagala
Proceedings of the 5th conference on Innovations in theoretical computer …, 2014
242014
Minimizing flow-time on unrelated machines
N Bansal, J Kulkarni
Proceedings of the forty-seventh annual ACM symposium on Theory of Computing …, 2015
232015
Privately learning Markov random fields
H Zhang, G Kamath, J Kulkarni, S Wu
International Conference on Machine Learning, 11129-11140, 2020
212020
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
212020
Private non-smooth empirical risk minimization and stochastic convex optimization in subquadratic steps
J Kulkarni, YT Lee, D Liu
arXiv preprint arXiv:2103.15352, 2021
202021
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