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 ...
It's no surprise that things break, but what is a surprise is that things — from ceramic plates to bubbles — all follow the same rule when breaking.
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: Many scheduling problems, especially for automated manufacturing systems, have been addressed with a timed Petri net (TPN) by developing optimal or heuristic algorithms based on it. However, ...
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 ...
Optimal Blue CEO Joe Tyrrell has responded to a class action lawsuit alleging mortgage price-fixing, calling the claims baseless and frivolous. The company, along with 26 major lenders, is accused of ...
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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