Practical Differentially Private Hyperparameter Tuning with Subsampling
Published in NeurIPS 2023, TrustML-(un)Limited@ICLR23, 2023
With Antti Koskela
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Publications
Locally Differentially Private Bayesian Inference
Published in Under review, 2021
With Joonas Jälkö, Samuel Kaski, and Antti Honkela
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Differentially Private Bayesian Inference for Generalized Linear Models
Published in ICML 2021, core A*, PPML 2021, 2021
With Joonas Jälkö, Antti Koskela, Antti Honkela, and Samuel Kaski
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Private Protocols for U-Statistics in the Local Model and Beyond
Published in AISTATS 2020, core A*, 2020
With James Bell, Aurélien Bellet, and Adrià Gascón
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Answering Range Queries Under Local Differential Privacy
Published in ACM VLDB 2019, core A*, student research competition @ SIGMOD 2019, 2019
With Graham Cormode and Divesh Srivastava
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Privacy at Scale: Local Differential Privacy in Practice
Published in Tutorial: ACM SIGMOD 2018, KDD 2018, 2018
With Graham Comrmode, Somesh Jha, Ninghui Li, Divesh Srivastava, Tianhao Wang
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Marginal Release Under Local Differential Privacy Model
Published in ACM SIGMOD 2018, core A*, 2018
With Graham Cormode and Divesh Srivastava
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Constrained Differential Privacy for Count Data
Published in IEEE ICDE 2018, best papers from ICDE 18 were invited for TKDE (IEEE Transactions on Knowledge and Data Engineering), core A*, 2018
With Graham Cormode and Divesh Srivastava
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Leader Election in Sparse Dynamic Networks with Churn
Published in IEEE IPDPS 2015, core A, 2015
With John Augustine and Sumathi Sivasubramaniam
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Robust Leader Election For Fast Changing World
Published in FOMC 2013 - A Workshop at ACM DISC 2013, 2013
With Paresh Nakhe, John Augustine, Peter Robinson
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