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 ...
Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
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 ...
Optimal Blue and dozens of lenders are poking holes in an antitrust case from borrowers, suggesting a core flaw in their claims in that the vendor doesn't operate a pricing algorithm. Processing ...
In the era of global energy transition, battery inverters have evolved from simple power conversion devices into core hubs that link renewable energy generation, energy storage systems (ESS), and ...
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 ...
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