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Best of Both Worlds Guarantees for Smoothed Online Quadratic Optimization
We provide the online optimal algorithm when the minimizers of the hitting cost function evolve as a general stochastic process, which, for the case of martingale process, takes the form of a distribution-agnostic dynamic interpolation algorithm (LAI).
Smoothed Online Optimization with Unreliable Predictions
The goal of the decision maker is to exploit the predictions if they are accurate, while guaranteeing performance that is not much worse than the hindsight optimal sequence of decisions, even when predictions are inaccurate.
Online Capacity Scaling Augmented With Unreliable Machine Learning Predictions
Modern data centers suffer from immense power consumption.
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