6 papers
Conformal Risk Training: End-to-End Optimization of Conformal Risk Control
Christopher Yeh, Nicolas Christianson, Adam Wierman +1
While deep learning models often achieve high predictive accuracy, their predictions typically do not come with any provable guarantees on risk or reliability, which are critical f…
Competitive Algorithms for Multi-Agent Ski-Rental Problems
Xuchuang Wang, Bo Sun, Hedyeh Beyhaghi +3
This paper introduces a novel multi-agent ski-rental problem that generalizes the classical ski-rental dilemma to a group setting where agents incur individual and shared costs. In…
Fast Non-Episodic Adaptive Tuning of Robot Controllers with Online Policy Optimization
James A. Preiss, Fengze Xie, Yiheng Lin +2
We study online algorithms to tune the parameters of a robot controller in a setting where the dynamics, policy class, and optimality objective are all time-varying. The system fol…
Maximizing the Value of Predictions in Control: Accuracy Is Not Enough
Yiheng Lin, Christopher Yeh, Zaiwei Chen +1
We study the value of stochastic predictions in online optimal control with random disturbances. Prior work provides performance guarantees based on prediction error but ignores th…
Fusing Reward and Dueling Feedback in Stochastic Bandits
Xuchuang Wang, Qirun Zeng, Jinhang Zuo +4
This paper investigates the fusion of absolute (reward) and relative (dueling) feedback in stochastic bandits, where both feedback types are gathered in each decision round. We der…
Carbon- and Precedence-Aware Scheduling for Data Processing Clusters
Adam Lechowicz, Rohan Shenoy, Noman Bashir +3
As large-scale data processing workloads continue to grow, their carbon footprint raises concerns. Prior research on carbon-aware schedulers has focused on shifting computation to…