no code implementations • 2 Jan 2024 • Piao Hu, Jiashuo Jiang, Guodong Lyu, Hao Su
When the model parameters are drawn from unknown non-stationary distributions and we are given machine-learned predictions of the distributions, we develop a new algorithm from our framework with a regret $O(W_T+\sqrt{T})$, where $W_T$ measures the total inaccuracy of the machine-learned predictions.