7 citations · 12 across the 6 of their papers we have counts for
6 papers
Learning-Augmented Competitive Algorithms for Spatiotemporal Online Allocation with Deadline Constraints
Adam Lechowicz, Nicolas Christianson, Bo Sun +4
We introduce and study spatiotemporal online allocation with deadline constraints (), a new online problem motivated by emerging challenges in sustainability and ene…
Near-Optimal Consistency-Robustness Trade-Offs for Learning-Augmented Online Knapsack Problems
Mohammadreza Daneshvaramoli, Helia Karisani, Adam Lechowicz +3
This paper introduces a family of learning-augmented algorithms for online knapsack problems that achieve near Pareto-optimal consistency-robustness trade-offs through a simple com…
Risk-Sensitive Online Algorithms
Nicolas Christianson, Bo Sun, Steven Low +1
We study the design of risk-sensitive online algorithms, in which risk measures are used in the competitive analysis of randomized online algorithms. We introduce the CVaR-comp…
Chasing Convex Functions with Long-term Constraints
Adam Lechowicz, Nicolas Christianson, Bo Sun +4
We introduce and study a family of online metric problems with long-term constraints. In these problems, an online player makes decisions in a metric space t…
Online Conversion with Switching Costs: Robust and Learning-Augmented Algorithms
Adam Lechowicz, Nicolas Christianson, Bo Sun +4
We introduce and study online conversion with switching costs, a family of online problems that capture emerging problems at the intersection of energy and sustainability. In this…
Online Algorithms with Uncertainty-Quantified Predictions
Bo Sun, Jerry Huang, Nicolas Christianson +3
The burgeoning field of algorithms with predictions studies the problem of using possibly imperfect machine learning predictions to improve online algorithm performance. While near…