7 citations · 17 across the 8 of their papers we have counts for
3 papers · 1 filter
Evaluating Robustness to Dataset Shift via Parametric Robustness Sets
Nikolaj Thams, Michael Oberst, David Sontag
We give a method for proactively identifying small, plausible shifts in distribution which lead to large differences in model performance. These shifts are defined via parametric c…
Invariant Policy Learning: A Causal Perspective
Sorawit Saengkyongam, Nikolaj Thams, Jonas Peters +1
Contextual bandit and reinforcement learning algorithms have been successfully used in various interactive learning systems such as online advertising, recommender systems, and dyn…
Regularizing towards Causal Invariance: Linear Models with Proxies
Michael Oberst, Nikolaj Thams, Jonas Peters +1
We propose a method for learning linear models whose predictive performance is robust to causal interventions on unobserved variables, when noisy proxies of those variables are ava…