3 papers
stat.ML2026
Invariance-Based Dynamic Regret Minimization
Margherita Lazzaretto, Jonas Peters, Niklas Pfister
We consider stochastic non-stationary linear bandits where the linear parameter connecting contexts to the reward changes over time. Existing algorithms in this setting localize th…
stat.ML2025
Boosted Control Functions: Distribution generalization and invariance in confounded models
Nicola Gnecco, Jonas Peters, Sebastian Engelke +1
Modern machine learning methods and the availability of large-scale data have significantly advanced our ability to predict target quantities from large sets of covariates. However…
stat.ML2025
Invariant Subspace Decomposition
Margherita Lazzaretto, Jonas Peters, Niklas Pfister
We consider the task of predicting a response Y from a set of covariates X in settings where the conditional distribution of Y given X changes over time. For this to be feasible, a…