activity
20112023
most citedBeyond Online Balanced Descent: An Optimal Algorithm for Smoothed Online Optimization

40 citations · 541 across the 88 of their papers we have counts for

collaborators

91 papers

cs.LG2023

Beyond Black-Box Advice: Learning-Augmented Algorithms for MDPs with Q-Value Predictions

Tongxin Li, Yiheng Lin, Shaolei Ren +1

We study the tradeoff between consistency and robustness in the context of a single-trajectory time-varying Markov Decision Process (MDP) with untrusted machine-learned advice. Our…

cs.AI2023★ 4 cited

Towards Environmentally Equitable AI via Geographical Load Balancing

Pengfei Li, Jianyi Yang, Adam Wierman +1

Fueled by the soaring popularity of large language and foundation models, the accelerated growth of artificial intelligence (AI) models' enormous environmental footprint has come u…

eess.SY2023★ 13 cited

Online learning for robust voltage control under uncertain grid topology

Christopher Yeh, Jing Yu, Yuanyuan Shi +1

Voltage control generally requires accurate information about the grid's topology in order to guarantee network stability. However, accurate topology identification is challenging…

cs.LG2023

Adversarial Attacks on Online Learning to Rank with Click Feedback

Jinhang Zuo, Zhiyao Zhang, Zhiyong Wang +3

Online learning to rank (OLTR) is a sequential decision-making problem where a learning agent selects an ordered list of items and receives feedback through user clicks. Although p…

math.OC2023★ 2 cited

Online Stabilization of Unknown Linear Time-Varying Systems

Jing Yu, Varun Gupta, Adam Wierman

This paper studies the problem of online stabilization of an unknown discrete-time linear time-varying (LTV) system under bounded non-stochastic (potentially adversarial) disturban…

cs.DS2023★ 22 cited

The Online Pause and Resume Problem: Optimal Algorithms and An Application to Carbon-Aware Load Shifting

Adam Lechowicz, Nicolas Christianson, Jinhang Zuo +4

We introduce and study the online pause and resume problem. In this problem, a player attempts to find the lowest (alternatively, highest) prices in a sequence of fixed length…