5 papers
Optimal Lower Bounds for Online Multicalibration
Natalie Collina, Jiuyao Lu, Georgy Noarov +1
We prove tight lower bounds for online multicalibration, establishing an information-theoretic separation from marginal calibration. In the general setting where group functions ca…
Multi-Objective Reinforcement Learning for Large-Scale Tote Allocation in Human-Robot Collaborative Fulfillment Centers
Sikata Sengupta, Guangyi Liu, Omer Gottesman +4
Optimizing the consolidation process in container-based fulfillment centers requires trading off competing objectives such as processing speed, resource usage, and space utilizatio…
Model Agreement via Anchoring
Eric Eaton, Surbhi Goel, Marcel Hussing +4
Numerous lines of aim to control -- the extent to which two machine learning models disagree in their predictions. We adopt a simple and standard noti…
Dynamic Regret Bounds for Online Omniprediction with Long Term Constraints
Yahav Bechavod, Jiuyao Lu, Aaron Roth
We present an algorithm guaranteeing dynamic regret bounds for online omniprediction with long term constraints. The goal in this recently introduced problem is for a learner to ge…
Online Omniprediction with Long-Term Constraints
Yahav Bechavod, Jiuyao Lu, Aaron Roth
We introduce and study the problem of online omniprediction with long-term constraints. At each round, a forecaster is tasked with generating predictions for an underlying (adaptiv…