12 citations · 23 across the 5 of their papers we have counts for
3 papers · 1 filter
Conditional Gradient Method for Stochastic Submodular Maximization: Closing the Gap
Aryan Mokhtari, Hamed Hassani, Amin Karbasi
In this paper, we study the problem of \textit{constrained} and \textit{stochastic} continuous submodular maximization. Even though the objective function is not concave (nor conve…
Stochastic Submodular Maximization: The Case of Coverage Functions
Mohammad Reza Karimi, Mario Lucic, Hamed Hassani +1
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 ob…
Uniform Deviation Bounds for Unbounded Loss Functions like k-Means
Olivier Bachem, Mario Lucic, S. Hamed Hassani +1
Uniform deviation bounds limit the difference between a model's expected loss and its loss on an empirical sample uniformly for all models in a learning problem. As such, they are…