Ravi Kumar
where else to find them
no profile links on file
what they talk about
all 5 in the filters
where they keep going back
- ITCS2 editions2021–2023
on a stage with
all 17 in the filters
who talks about the same things
- Badih Ghazi4 talks
- Pasin Manurangsi8 talks
- Sriram Narayan4 talks
- Varun Gupta7 talks
- Vaidik Kapoor4 talks
- Doc Norton10 talks
| title | conference | date |
|---|---|---|
| A DP Framework for Gaining Insights into AI Chatbot Use | PEPR '26 | 2026-06-01 |
Urania converts millions of raw chatbot logs into DP-safe summaries and trends, claiming end-to-end ε,δ DP guarantees by privatizing cluster centers and… | ||
| Algorithms with More Granular Differential Privacy Guarantees | ITCS 2023 | 2023-01-10 |
Defines per-attribute differential privacy and gives concrete algorithms that trade per-person epsilon for much smaller per-attribute epsilon0. Uses Gaussian… | ||
| Private Counting of Distinct and k-Occurring Items in Time Windows | ITCS 2023 | 2023-01-10 |
Paper gives private algorithms for counting distinct and k-occurring items over time windows by reducing these queries to differentially private range queries… | ||
| Parsimonious Learning-Augmented Algorithms | Quantifying Uncertainty: Stochastic, Adversarial, and Beyond | 2022-09-12 |
New results show a sublinear number of predictions suffices for meaningful gains. For online linear optimization a randomized algorithm combines FTRL with a… | ||
| On Distributed Differential Privacy and Counting Distinct Elements | ITCS 2021 | 2021-01-06 |
Shows that distinct counting under constant-epsilon, delta = 1/poly(n) privacy is basically impossible in the local model: any local protocol needs error ≈ N /… | ||
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