2017
Stochastic Submodular Maximization: The Case of Coverage Functions
NeurIPS 2017poster
Stochastic optimization of continuous objectives is at the heart of modern machine learning. However, many important problems are of discrete nature and often involve submodular objectives. We seek to unleash the power of stochastic continuous optimization, namely stochastic gradient descent and its…