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ORCIDJalaj Upadhyay
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2020 – today
- 2025
[c19]Monika Henzinger, Jalaj Upadhyay:
Improved Differentially Private Continual Observation Using Group Algebra. SODA 2025: 2951-2970- 2024
- [c18]Greg Bodwin, Chengyuan Deng, Jie Gao, Gary Hoppenworth, Jalaj Upadhyay, Chen Wang:
The Discrepancy of Shortest Paths. ICALP 2024: 27:1-27:20 - [c17]Edwige Cyffers, Aurélien Bellet, Jalaj Upadhyay:
Differentially Private Decentralized Learning with Random Walks. ICML 2024 - [c16]Monika Henzinger, Jalaj Upadhyay, Sarvagya Upadhyay:
A Unifying Framework for Differentially Private Sums under Continual Observation. SODA 2024: 995-1018 - [c15]Jingcheng Liu, Jalaj Upadhyay, Zongrui Zou:
Optimal Bounds on Private Graph Approximation. SODA 2024: 1019-1049 - [i27]Greg Bodwin, Chengyuan Deng, Jie Gao, Gary Hoppenworth, Jalaj Upadhyay, Chen Wang:
The Discrepancy of Shortest Paths. CoRR abs/2401.15781 (2024) - [i26]Edwige Cyffers, Aurélien Bellet, Jalaj Upadhyay:
Differentially Private Decentralized Learning with Random Walks. CoRR abs/2402.07471 (2024) - [i25]Jingcheng Liu, Jalaj Upadhyay, Zongrui Zou:
Optimality of Matrix Mechanism on ℓpp-metric. CoRR abs/2406.02140 (2024) - [i24]Jingcheng Liu, Jalaj Upadhyay, Zongrui Zou:
Almost linear time differentially private release of synthetic graphs. CoRR abs/2406.02156 (2024) - [i23]Joel Daniel Andersson, Monika Henzinger, Rasmus Pagh, Teresa Anna Steiner, Jalaj Upadhyay:
Continual Counting with Gradual Privacy Expiration. CoRR abs/2406.03802 (2024) - [i22]Monika Henzinger, Jalaj Upadhyay:
Improved Differentially Private Continual Observation Using Group Algebra. CoRR abs/2412.02840 (2024) - 2023
- [c14]Arun Ganesh, Abhradeep Thakurta, Jalaj Upadhyay:
Universality of Langevin Diffusion for Private Optimization, with Applications to Sampling from Rashomon Sets. COLT 2023: 1730-1773 - [c13]Hendrik Fichtenberger, Monika Henzinger, Jalaj Upadhyay:
Constant Matters: Fine-grained Error Bound on Differentially Private Continual Observation. ICML 2023: 10072-10092 - [c12]Monika Henzinger, Jalaj Upadhyay, Sarvagya Upadhyay:
Almost Tight Error Bounds on Differentially Private Continual Counting. SODA 2023: 5003-5039 - [c11]Chengyuan Deng, Jie Gao, Jalaj Upadhyay, Chen Wang:
Differentially Private Range Query on Shortest Paths. WADS 2023: 340-370 - [i21]Monika Henzinger, Jalaj Upadhyay, Sarvagya Upadhyay:
A Unifying Framework for Differentially Private Sums under Continual Observation. CoRR abs/2307.08970 (2023) - [i20]Jingcheng Liu, Jalaj Upadhyay, Zongrui Zou:
Optimal Bounds on Private Graph Approximation. CoRR abs/2309.17330 (2023) - 2022
- [i19]Monika Henzinger, Jalaj Upadhyay:
Constant matters: Fine-grained Complexity of Differentially Private Continual Observation Using Completely Bounded Norms. CoRR abs/2202.11205 (2022) - [i18]Arun Ganesh, Abhradeep Thakurta, Jalaj Upadhyay:
Langevin Diffusion: An Almost Universal Algorithm for Private Euclidean (Convex) Optimization. CoRR abs/2204.01585 (2022) - [i17]Monika Henzinger, Jalaj Upadhyay, Sarvagya Upadhyay:
Almost Tight Error Bounds on Differentially Private Continual Counting. CoRR abs/2211.05006 (2022) - [i16]Monika Henzinger, Jalaj Upadhyay:
Constant matters: Fine-grained Complexity of Differentially Private Continual Observation Using Completely Bounded Norms. IACR Cryptol. ePrint Arch. 2022: 225 (2022) - 2021
- [c10]Jalaj Upadhyay, Sarvagya Upadhyay, Raman Arora:
Differentially Private Analysis on Graph Streams. AISTATS 2021: 1171-1179 - [c9]Jalaj Upadhyay, Sarvagya Upadhyay:
A Framework for Private Matrix Analysis in Sliding Window Model. ICML 2021: 10465-10475 - 2020
- [c8]Vladimir Braverman, Petros Drineas, Cameron Musco, Christopher Musco, Jalaj Upadhyay, David P. Woodruff, Samson Zhou:
Near Optimal Linear Algebra in the Online and Sliding Window Models. FOCS 2020: 517-528 - [i15]Jalaj Upadhyay, Sarvagya Upadhyay:
A Framework for Private Matrix Analysis. CoRR abs/2009.02668 (2020)
2010 – 2019
- 2019
- [c7]Jalaj Upadhyay:
Sublinear Space Private Algorithms Under the Sliding Window Model. ICML 2019: 6363-6372 - [c6]Raman Arora, Jalaj Upadhyay:
On Differentially Private Graph Sparsification and Applications. NeurIPS 2019: 13378-13389 - 2018
- [j5]Maura B. Paterson
, Douglas R. Stinson, Jalaj Upadhyay:
Multi-prover proof of retrievability. J. Math. Cryptol. 12(4): 203-220 (2018) - [c5]Raman Arora, Vladimir Braverman, Jalaj Upadhyay:
Differentially Private Robust Low-Rank Approximation. NeurIPS 2018: 4141-4149 - [c4]Jalaj Upadhyay:
The Price of Privacy for Low-rank Factorization. NeurIPS 2018: 4180-4191 - [i14]Vladimir Braverman, Petros Drineas, Cameron Musco, Christopher Musco, Jalaj Upadhyay, David P. Woodruff, Samson Zhou:
Near Optimal Linear Algebra in the Online and Sliding Window Models. CoRR abs/1805.03765 (2018) - 2017
- [c3]Adam D. Smith, Abhradeep Thakurta, Jalaj Upadhyay:
Is Interaction Necessary for Distributed Private Learning? IEEE Symposium on Security and Privacy 2017: 58-77 - 2016
- [j4]Jalaj Upadhyay:
Review of: Distributed Computing Through Combinatorial Topology by Maurice Herlihy and Dmitry Kozlov and Sergio Rajsbaum. SIGACT News 47(2): 18-20 (2016) - [c2]Nishanth Chandran, Vipul Goyal, Pratyay Mukherjee, Omkant Pandey, Jalaj Upadhyay:
Block-Wise Non-Malleable Codes. ICALP 2016: 31:1-31:14 - [i13]Maura B. Paterson, Douglas R. Stinson, Jalaj Upadhyay:
Multi-prover Proof-of-Retrievability. CoRR abs/1603.02671 (2016) - [i12]Jalaj Upadhyay:
Fast and Space-optimal Low-rank Factorization in the Streaming Model With Application in Differential Privacy. CoRR abs/1604.01429 (2016) - [i11]Jalaj Upadhyay:
On Low-Space Differentially Private Low-rank Factorization in the Spectral Norm. CoRR abs/1611.08954 (2016) - [i10]Maura B. Paterson, Douglas R. Stinson, Jalaj Upadhyay:
Multi-prover Proof-of-Retrievability. IACR Cryptol. ePrint Arch. 2016: 265 (2016) - 2015
- [b1]Jalaj Upadhyay:
Integrity and Privacy of Large Data. University of Waterloo, Ontario, Canada, 2015 - [i9]Nishanth Chandran, Vipul Goyal, Pratyay Mukherjee, Omkant Pandey, Jalaj Upadhyay:
Block-wise Non-Malleable Codes. IACR Cryptol. ePrint Arch. 2015: 129 (2015) - 2014
- [j3]Douglas R. Stinson, Jalaj Upadhyay:
Is extracting data the same as possessing data? J. Math. Cryptol. 8(2): 189-207 (2014) - [i8]Jalaj Upadhyay:
Differentially Private Linear Algebra in the Streaming Model. CoRR abs/1409.5414 (2014) - [i7]Jalaj Upadhyay:
Circulant Matrices and Differential Privacy. CoRR abs/1410.2470 (2014) - [i6]Jalaj Upadhyay:
Differentially Private Linear Algebra in the Streaming Model. IACR Cryptol. ePrint Arch. 2014: 730 (2014) - 2013
- [j2]Maura B. Paterson, Douglas R. Stinson, Jalaj Upadhyay:
A coding theory foundation for the analysis of general unconditionally secure proof-of-retrievability schemes for cloud storage. J. Math. Cryptol. 7(3): 183-216 (2013) - [c1]Jalaj Upadhyay:
Random Projections, Graph Sparsification, and Differential Privacy. ASIACRYPT (1) 2013: 276-295 - [i5]Jalaj Upadhyay:
Random Projections, Graph Sparsification, and Differential Privacy. IACR Cryptol. ePrint Arch. 2013: 580 (2013) - [i4]Douglas R. Stinson, Jalaj Upadhyay:
Is extracting data the same as possessing data? IACR Cryptol. ePrint Arch. 2013: 614 (2013) - 2012
- [j1]Simon R. Blackburn, Douglas R. Stinson, Jalaj Upadhyay:
On the complexity of the herding attack and some related attacks on hash functions. Des. Codes Cryptogr. 64(1-2): 171-193 (2012) - [i3]Maura B. Paterson, Douglas R. Stinson, Jalaj Upadhyay:
A coding theory foundation for the analysis of general unconditionally secure proof-of-retrievability schemes for cloud storage. CoRR abs/1210.7756 (2012) - [i2]Maura B. Paterson, Douglas R. Stinson, Jalaj Upadhyay:
A coding theory foundation for the analysis of general unconditionally secure proof-of-retrievability schemes for cloud storage. IACR Cryptol. ePrint Arch. 2012: 611 (2012) - 2010
- [i1]Simon R. Blackburn, Douglas R. Stinson, Jalaj Upadhyay:
On the Complexity of the Herding Attack and Some Related Attacks on Hash Functions. IACR Cryptol. ePrint Arch. 2010: 30 (2010)
Coauthor Index
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