3 citations · 3 across the 8 of their papers we have counts for
3 papers · 1 filter
Online Learning on Hidden-Convex Losses via Algorithmic Equivalence: Optimal Regret, Geometric Barrier, and Bandit Feedback
Anas Barakat, Andreas Kontogiannis, Vasilis Pollatos +2
We study adversarial online learning with hidden-convex losses, i.e., nonconvex losses that become convex after a nonlinear reparameterization. Ghai, Lu and Hazan (2022) proved tha…
Efficient Swap Regret Minimization in Combinatorial Bandits
Andreas Kontogiannis, Vasilis Pollatos, Panayotis Mertikopoulos +1
This paper addresses the problem of designing efficient no-swap regret algorithms for combinatorial bandits, where the number of actions is exponentially large in the dimension…
On Corruption-Robustness in Performative Reinforcement Learning
Vasilis Pollatos, Debmalya Mandal, Goran Radanovic
In performative Reinforcement Learning (RL), an agent faces a policy-dependent environment: the reward and transition functions depend on the agent's policy. Prior work on performa…