32 citations · 32 across the 1 of their papers we have counts for
2 papers
cs.LG2020
Enabling Fast Differentially Private SGD via Just-in-Time Compilation and Vectorization
Pranav Subramani, Nicholas Vadivelu, Gautam Kamath
A common pain point in differentially private machine learning is the significant runtime overhead incurred when executing Differentially Private Stochastic Gradient Descent (DPSGD…
cs.LG2019★ 32 cited
SPFlow: An Easy and Extensible Library for Deep Probabilistic Learning using Sum-Product Networks
Alejandro Molina, Antonio Vergari, Karl Stelzner +5
We introduce SPFlow, an open-source Python library providing a simple interface to inference, learning and manipulation routines for deep and tractable probabilistic models called…