Optimally Pacing Budget Spending and Learning
The paper analyzes online learning with budget constraints, where a learner must spend a fixed amount before stopping. It shows that optimal regret bounds depend on the distance between expert spending patterns, suggesting fractional play and specific allocation strategies can achieve near-optimal performance against adversarial experts.