989 citations · 4.1k across the 80 of their papers we have counts for
6 papers · 2 filters
Learning User Preferences to Incentivize Exploration in the Sharing Economy
Christoph Hirnschall, Adish Singla, Sebastian Tschiatschek +1
We study platforms in the sharing economy and discuss the need for incentivizing users to explore options that otherwise would not be chosen. For instance, rental platforms such as…
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…
Continuous DR-submodular Maximization: Structure and Algorithms
An Bian, Kfir Y. Levy, Andreas Krause +1
DR-submodular continuous functions are important objectives with wide real-world applications spanning MAP inference in determinantal point processes (DPPs), and mean-field inferen…
An Online Learning Approach to Generative Adversarial Networks
Paulina Grnarova, Kfir Y. Levy, Aurelien Lucchi +2
We consider the problem of training generative models with a Generative Adversarial Network (GAN). Although GANs can accurately model complex distributions, they are known to be di…
Learning to Use Learners' Advice
Adish Singla, Hamed Hassani, Andreas Krause
In this paper, we study a variant of the framework of online learning using expert advice with limited/bandit feedback. We consider each expert as a learning entity, seeking to mor…
Coordinated Online Learning With Applications to Learning User Preferences
Christoph Hirnschall, Adish Singla, Sebastian Tschiatschek +1
We study an online multi-task learning setting, in which instances of related tasks arrive sequentially, and are handled by task-specific online learners. We consider an algorithmi…