4 papers · 1 filter
Schrödinger bridge with transport relaxation
Yifan Jiang, Renyuan Xu, Luhao Zhang
Motivated by modern machine learning applications where we only have access to empirical measures constructed from finite samples, we relax the marginal constraints of the classica…
Duality of causal distributionally robust optimization
Yifan Jiang
We study distributionally robust optimization (DRO) in a dynamic context, where model uncertainty is captured by penalizing potential models based on their adapted Wasserstein dist…
A transfer principle for computing the adapted Wasserstein distance between stochastic processes
Yifan Jiang, Fang Rui Lim
We propose a transfer principle to study the adapted 2-Wasserstein distance between stochastic processes. First, we obtain an explicit formula for the distance between real-valued…
Sensitivity of causal distributionally robust optimization
Yifan Jiang, Jan Obloj
We study the causal distributionally robust optimization (DRO) in both discrete- and continuous- time settings. The framework captures model uncertainty, with potential models pena…