Shiva Kasiviswanathan

About Me:

Principal Applied Scientist at Amazon, Bay Area, California

Research Interests:

Machine Learning, Deep Learning, Data Privacy, Causal Inference, Design and Analysis of Algorithms

Selected Publications (All Publications)

• Debiasing Conditional Stochastic Optimization
        With L. He. In NeurIPS 2023.
• Thompson Sampling with Diffusion Generative Prior
        With Y. Hsieh, B. Kveton, and P. Bloebaum. In ICML 2023.
• 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.
• 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.