On the complexity of the herding attack and some related attacks on hash functions. - Simon R. Blackburn; Douglas R. Stinson; Jalaj Upadhyay (Des. Codes Cryptogr., 2012)

Random Projections, Graph Sparsification, and Differential Privacy. - Jalaj Upadhyay (IACR Cryptol. ePrint Arch., 2013)

A coding theory foundation for the analysis of general unconditionally secure proof-of-retrievability schemes for cloud storage. - Maura B. Paterson; Douglas R. Stinson; Jalaj Upadhyay (J. Math. Cryptol., 2013)

Circulant Matrices and Differential Privacy. - Jalaj Upadhyay (CoRR, 2014)

Differentially Private Linear Algebra in the Streaming Model. - Jalaj Upadhyay (IACR Cryptol. ePrint Arch., 2014)

Is extracting data the same as possessing data? - Douglas R. Stinson; Jalaj Upadhyay (J. Math. Cryptol., 2014)

Block-wise Non-Malleable Codes. - Nishanth Chandran; Vipul Goyal; Pratyay Mukherjee; Omkant Pandey; Jalaj Upadhyay (IACR Cryptol. ePrint Arch., 2015)

Integrity and Privacy of Large Data. - Jalaj Upadhyay (2015)

Fast and Space-optimal Low-rank Factorization in the Streaming Model With Application in Differential Privacy. - Jalaj Upadhyay (CoRR, 2016)

On Low-Space Differentially Private Low-rank Factorization in the Spectral Norm. - Jalaj Upadhyay (CoRR, 2016)

Review of: Distributed Computing Through Combinatorial Topology by Maurice Herlihy and Dmitry Kozlov and Sergio Rajsbaum. - Jalaj Upadhyay (SIGACT News, 2016)

Is Interaction Necessary for Distributed Private Learning? - Adam D. Smith 001; Abhradeep Thakurta; Jalaj Upadhyay (IEEE Symposium on Security and Privacy, 2017)

Differentially Private Robust Low-Rank Approximation. - Raman Arora; Vladimir Braverman; Jalaj Upadhyay (NeurIPS, 2018)

The Price of Privacy for Low-rank Factorization. - Jalaj Upadhyay (NeurIPS, 2018)

Multi-prover proof of retrievability. - Maura B. Paterson; Douglas R. Stinson; Jalaj Upadhyay (J. Math. Cryptol., 2018)

Sublinear Space Private Algorithms Under the Sliding Window Model. - Jalaj Upadhyay (ICML, 2019)

On Differentially Private Graph Sparsification and Applications. - Raman Arora; Jalaj Upadhyay (NeurIPS, 2019)

Near Optimal Linear Algebra in the Online and Sliding Window Models. - Vladimir Braverman; Petros Drineas; Cameron Musco; Christopher Musco; Jalaj Upadhyay; David P. Woodruff; Samson Zhou (FOCS, 2020)

A Framework for Private Matrix Analysis. - Jalaj Upadhyay; Sarvagya Upadhyay (CoRR, 2020)

Differentially Private Analysis on Graph Streams. - Jalaj Upadhyay; Sarvagya Upadhyay; Raman Arora (AISTATS, 2021)

A Framework for Private Matrix Analysis in Sliding Window Model. - Jalaj Upadhyay; Sarvagya Upadhyay (ICML, 2021)

Langevin Diffusion: An Almost Universal Algorithm for Private Euclidean (Convex) Optimization. - Arun Ganesh; Abhradeep Thakurta; Jalaj Upadhyay (CoRR, 2022)

Constant matters: Fine-grained Complexity of Differentially Private Continual Observation Using Completely Bounded Norms. - Monika Henzinger; Jalaj Upadhyay (IACR Cryptol. ePrint Arch., 2022)

Universality of Langevin Diffusion for Private Optimization, with Applications to Sampling from Rashomon Sets. - Arun Ganesh; Abhradeep Thakurta; Jalaj Upadhyay (COLT, 2023)

Constant Matters: Fine-grained Error Bound on Differentially Private Continual Observation. - Hendrik Fichtenberger; Monika Henzinger; Jalaj Upadhyay (ICML, 2023)

Almost Tight Error Bounds on Differentially Private Continual Counting. - Monika Henzinger; Jalaj Upadhyay; Sarvagya Upadhyay (SODA, 2023)

Differentially Private Range Query on Shortest Paths. - Chengyuan Deng; Jie Gao 001; Jalaj Upadhyay; Chen Wang 027 (WADS, 2023)

The Discrepancy of Shortest Paths. - Greg Bodwin; Chengyuan Deng; Jie Gao 001; Gary Hoppenworth; Jalaj Upadhyay; Chen Wang 027 (ICALP, 2024)

Differentially Private Decentralized Learning with Random Walks. - Edwige Cyffers; Aurélien Bellet; Jalaj Upadhyay (ICML, 2024)

Continual Counting with Gradual Privacy Expiration. - Joel Daniel Andersson; Monika Henzinger; Rasmus Pagh; Teresa Anna Steiner; Jalaj Upadhyay (NeurIPS, 2024)

A Unifying Framework for Differentially Private Sums under Continual Observation. - Monika Henzinger; Jalaj Upadhyay; Sarvagya Upadhyay (SODA, 2024)

Optimal Bounds on Private Graph Approximation. - Jingcheng Liu 001; Jalaj Upadhyay; Zongrui Zou (SODA, 2024)

Optimality of Matrix Mechanism on ℓpp-metric. - Jingcheng Liu 001; Jalaj Upadhyay; Zongrui Zou (CoRR, 2024)

Almost linear time differentially private release of synthetic graphs. - Zongrui Zou; Jingcheng Liu 001; Jalaj Upadhyay (AISTATS, 2025)

On the Price of Differential Privacy for Hierarchical Clustering. - Chengyuan Deng; Jie Gao 001; Jalaj Upadhyay; Chen Wang 027; Samson Zhou (ICLR, 2025)

Optimality of Matrix Mechanism on ℓpp-metric. - Zongrui Zou; Jingcheng Liu 001; Jalaj Upadhyay (ICLR, 2025)

Improved Differentially Private Continual Observation Using Group Algebra. - Monika Henzinger; Jalaj Upadhyay (SODA, 2025)

Continual Release Moment Estimation with Differential Privacy. - Nikita P. Kalinin; Jalaj Upadhyay; Christoph H. Lampert (CoRR, 2025)

A Generalized Binary Tree Mechanism for Differentially Private Approximation of All-Pair Distances. - Michael Dinitz; Chenglin Fan; Jingcheng Liu 001; Jalaj Upadhyay; Zongrui Zou (CoRR, 2025)

Binned Group Algebra Factorization for Differentially Private Continual Counting. - Monika Henzinger; Nikita P. Kalinin; Jalaj Upadhyay (CoRR, 2025)

Back to Square Roots: An Optimal Bound on the Matrix Factorization Error for Multi-Epoch Differentially Private SGD. - Nikita P. Kalinin; Ryan McKenna; Jalaj Upadhyay; Christoph H. Lampert (CoRR, 2025)

Correlated Noise Mechanisms for Differentially Private Learning. - Krishna Pillutla; Jalaj Upadhyay; Christopher A. Choquette-Choo; Krishnamurthy Dvijotham; Arun Ganesh; Monika Henzinger; Jonathan Katz; Ryan McKenna; H. Brendan McMahan; Keith Rush; Thomas Steinke 002; Abhradeep Thakurta (CoRR, 2025)