PaperTseng et al. 2025
Tseng et al. 2025 Algorithm
An online learning algorithm for quantum states proposed by Tseng et al. in 2025, whose regret rate matches the lower bound proven in this work in terms of polynomial dependence on dimension d, achieving minimax optimality.
Timeline (last 90 days)
Oct 16
The regret rates of the exponentiated weights algorithm and the algorithm of Tseng et al. (2025) are already optimal in their polynomial dependence on the dimension d, matching the lower bound.
Unverified50%