Kasiviswanathan, Shiva Prasad

10 publications

UAI 2021 SGD with Low-Dimensional Gradients with Applications to Private and Distributed Learning Shiva Prasad Kasiviswanathan

AISTATS 2019 Subsampled Renyi Differential Privacy and Analytical Moments Accountant Yu-Xiang Wang, Borja Balle, Shiva Prasad Kasiviswanathan

IJCAI 2018 Network Approximation Using Tensor Sketching Shiva Prasad Kasiviswanathan, Nina Narodytska, Hongxia Jin

COLT 2018 Restricted Eigenvalue from Stable Rank with Applications to Sparse Linear Regression Shiva Prasad Kasiviswanathan, Mark Rudelson

AAAI 2018 Verifying Properties of Binarized Deep Neural Networks Nina Narodytska, Shiva Prasad Kasiviswanathan, Leonid Ryzhyk, Mooly Sagiv, Toby Walsh

CVPRW 2017 Simple Black-Box Adversarial Attacks on Deep Neural Networks Nina Narodytska, Shiva Prasad Kasiviswanathan

ICML 2016 Efficient Private Empirical Risk Minimization for High-Dimensional Learning Shiva Prasad Kasiviswanathan, Hongxia Jin

AAAI 2015 Online Dictionary Learning on Symmetric Positive Definite Manifolds with Vision Applications Shengping Zhang, Shiva Prasad Kasiviswanathan, Pong C. Yuen, Mehrtash Harandi

MLJ 2014 Bounds on the Sample Complexity for Private Learning and Private Data Release Amos Beimel, Hai Brenner, Shiva Prasad Kasiviswanathan, Kobbi Nissim

ICML 2012 Efficient and Practical Stochastic Subgradient Descent for Nuclear Norm Regularization Haim Avron, Satyen Kale, Shiva Prasad Kasiviswanathan, Vikas Sindhwani