Jacob Imola

According to our database, Jacob Imola authored at least 12 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Private estimation algorithms for stochastic block models and mixture models.

Hongjie Chen, Vincent Cohen-Addad, Tommaso d'Orsi, Alessandro Epasto, Jacob Imola, David Steurer, Stefan Tiegel

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Differentially Private Hierarchical Clustering with Provable Approximation Guarantees.

Jacob Imola, Alessandro Epasto, Mohammad Mahdian, Vincent Cohen-Addad, Vahab Mirrokni

Proceedings of the International Conference on Machine Learning, 2023

Online k-means Clustering on Arbitrary Data Streams.

Robi Bhattacharjee, Jacob Imola, Michal Moshkovitz, Sanjoy Dasgupta

Proceedings of the International Conference on Algorithmic Learning Theory, 2023

2022

Robustness of Locally Differentially Private Graph Analysis Against Poisoning.

Jacob Imola, Amrita Roy Chowdhury, Kamalika Chaudhuri

CoRR, 2022

Differentially Private Subgraph Counting in the Shuffle Model.

Jacob Imola, Takao Murakami, Kamalika Chaudhuri

CoRR, 2022

Communication-Efficient Triangle Counting under Local Differential Privacy.

Jacob Imola, Takao Murakami, Kamalika Chaudhuri

Proceedings of the 31st USENIX Security Symposium, 2022

Balancing utility and scalability in metric differential privacy.

Jacob Imola, Shiva Prasad Kasiviswanathan, Stephen White, Abhinav Aggarwal, Nathanael Teissier

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Differentially Private Triangle and 4-Cycle Counting in the Shuffle Model.

Jacob Imola, Takao Murakami, Kamalika Chaudhuri

Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, 2022

2021

Privacy Amplification Via Bernoulli Sampling.

Jacob Imola, Kamalika Chaudhuri

CoRR, 2021

No-Substitution $k$-means Clustering with Low Center Complexity and Memory.

Robi Bhattacharjee, Jacob Imola

CoRR, 2021

Locally Differentially Private Analysis of Graph Statistics.

Jacob Imola, Takao Murakami, Kamalika Chaudhuri

Proceedings of the 30th USENIX Security Symposium, 2021

2019

Capacity Bounded Differential Privacy.

Kamalika Chaudhuri, Jacob Imola, Ashwin Machanavajjhala

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019