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HSRL is a novel reinforcement learning framework for recommender systems that addresses one of the most critical bottlenecks in RL-based recommendation — the dynamic and high-dimensional action space.

Understand Thevenin’s Theorem the easy way with a clear, step-by-step circuit example. Learn how to simplify complex electrical networks into an equivalent circuit, making analysis faster and ...

This project investigates data curation strategies to solve the long-tail problem in autonomous driving. Standard Offline RL agents, trained on the raw, imbalanced data distribution, often fail in ...

The sea ice changed completely over the course of a few hours, from disconnected floes to a vast, snow-covered plain. By Raymond Zhong Most of the reserves in the country are extra-heavy oil that’s ...

Daniel Liberto is a journalist with over 10 years of experience working with publications such as the Financial Times, The Independent, and Investors Chronicle. Robert Kelly is managing director of ...

Katrina Ávila Munichiello is an experienced editor, writer, fact-checker, and proofreader with more than fourteen years of experience working with print and online publications. Investopedia / Lara ...

Insights from data and ML algorithms can be invaluable, but be warned — mistakes can be irreversible. These recent high-profile AI blunders illustrate the damage done when things don’t go according to ...