8 citations · 25 across the 10 of their papers we have counts for
3 papers · 1 filter
Statistical, Robustness, and Computational Guarantees for Sliced Wasserstein Distances
Sloan Nietert, Ritwik Sadhu, Ziv Goldfeld +1
Sliced Wasserstein distances preserve properties of classic Wasserstein distances while being more scalable for computation and estimation in high dimensions. The goal of this work…
Learning in Stackelberg Games with Non-myopic Agents
Nika Haghtalab, Thodoris Lykouris, Sloan Nietert +1
We study Stackelberg games where a principal repeatedly interacts with a non-myopic long-lived agent, without knowing the agent's payoff function. Although learning in Stackelberg…
Limit distribution theory for smooth -Wasserstein distances
Ziv Goldfeld, Kengo Kato, Sloan Nietert +1
The Wasserstein distance is a metric on a space of probability measures that has seen a surge of applications in statistics, machine learning, and applied mathematics. However, sta…