The modern workplace is constantly evolving, making skill development essential. Ongoing learning and a clear personal plan ...

Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...

Machine learning algorithms can predict which candidates are more likely to succeed in a given role by analyzing past hiring ...

Abstract: Multi-objective reinforcement learning (MORL) is a structured approach for optimizing tasks with multiple objectives. However, it often relies on pre-defined reward functions, which can be ...

Rick: A lot of parents and educators may be familiar with the phrase “mastery learning” but not have a clear idea what it means in practice. What is it exactly? Scott: My journey began in 2012 when I ...

Rick: A lot of parents and educators may be familiar with the phrase “mastery learning” but not have a clear idea what it means in practice. What is it exactly? Scott: My journey began in 2012 when I ...

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...

Does TRL support multi-objective reinforcement learning to align a large language model? For example, if we want to align a machine translation model to maximize three metrics: faithfulness, ...

1 Research Institute of Petroleum Exploration and Development, PetroChina, Beijing, China 2 Faculty of Petroleum, China University of Petroleum-Beijing at Karamay, Karamay, China Lithology ...

Most K-12 schools in the US will continue to use learning management systems (LMSs) to deliver learning materials, including documents, videos, and quizzes. 1 Look one level deeper, however, and the ...