Tension: Marketers expect consistent ad performance, but audiences process the same message with decreasing intensity over ...
Tension: Marketers keep optimizing for yesterday’s algorithms while platforms have quietly rewritten the rules of visibility ...
From autonomous cars to video games, reinforcement learning (machine learning through interaction with environments) can have ...
Machine learning systems embed preferences either in training losses or through post-processing of calibrated predictions. Applying information design methods from Strack and Yang (2024), this paper ...
The original version of this story appeared in Quanta Magazine. In 1939, upon arriving late to his statistics course at UC Berkeley, George Dantzig—a first-year graduate student—copied two problems ...
Abstract: This article investigates the distributed optimal coordination problem and distributed constrained optimal coordination problem for multiple heterogeneous linear systems over a directed ...
Copyright: © 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. We developed an open-source ...
Mortgage-pricing data has gone digital. But when does transparency turn into coordination? In early October 2025, mortgage-technology provider Optimal Blue and three major lenders were sued in a ...
A new class-action lawsuit against Optimal Blue mirrors the RealPage and real estate commission lawsuits, alleging lenders used the firm’s pricing software to coordinate mortgage rates through shared ...
Abstract: In this article, we propose a novel online learning algorithm based on weighted policy iteration (WPI) for addressing optimal control problems of nonlinear systems. WPI is proposed to deal ...
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