Search Results for author:
Found 4 papers, 0 papers with code
A Unifying Framework for Online Optimization with Long-Term Constraints
We present the first best-of-both-world type algorithm for this general class of problems, with no-regret guarantees both in the case in which rewards and constraints are selected according to an unknown stochastic model, and in the case in which they are selected at each round by an adversary.
Multi-Armed Bandit Problem with Temporally-Partitioned Rewards: When Partial Feedback Counts
We provide two algorithms to address TP-MAB problems, namely, TP-UCB-FR and TP-UCB-EW, which exploit the partial information disclosed by the reward collected over time.
Safe Online Bid Optimization with Return-On-Investment and Budget Constraints subject to Uncertainty
More interestingly, we provide an algorithm, namely GCB_{safe}(\psi,\phi), guaranteeing both sublinear pseudo-regret and safety w. h. p.
Online Posted Pricing with Unknown Time-Discounted Valuations
We evaluate our mechanisms in terms of competitive ratio, measuring the worst-case ratio between their revenue and that of an optimal mechanism that knows the distribution of valuations.
Computer Science and Game Theory
