About Me:
Senior Applied Scientist at Amazon, Bay Area, California
Visitor Simons Institute Causality Program, Berkeley (Spring 2022)
Research Interests:
Machine Learning, Deep Learning, Data Privacy, Causality, Design and Analysis of Algorithms
Selected Publications (All Publications)
- Collaborative Causal Discovery with Atomic Interventions
With R. Addanki. In NeurIPS 2021. - Subsampled Renyi Differential Privacy and Analytical Moments Accountant
With Y. Wang and B. Balle. In AISTATS 2019 (Notable Paper Award) - Restricted Eigenvalue from Stable Rank with Applications to Sparse Linear Regression
With M. Rudelson. In COLT 2018 - Efficient Private Empirical Risk Minimization for High-dimensional Learning
With H. Jin. In ICML 2016 - Streaming Anomaly Detection Using Randomized Matrix Sketching
With H. Huang. In VLDB 2016 - The Price of Privately Releasing Contingency Tables and the Spectra of Random Matrices with Correlated Rows
With M. Rudelson, A. Smith, and J. Ullman. In STOC 2010. - What Can We Learn Privately?
With H. K. Lee, K. Nissim, S. Raskhodnikova, and A. Smith. In SICOMP 2011, FOCS 2008.
