Department leaders in long-term care organizations often find themselves in a balancing act. They’re responsible for leading their teams while also being ...

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 ...

Why AI’s real failure isn’t intelligence but memory and how broken continuity is quietly undermining advertising performance.

of children under 9 could articulate a specific future job, long before subject choices, career guidance or college courses ...

As kids head back to school and attention returns to the daily grind of lunch boxes, new research reveals Australian parents ...

Senior living providers are shifting their engagement and wellness to focus on personalization, independence and choice as the boomers arrive at their ...

Tecnic instructors receive specialized training in working with different age groups, understanding that a teaching method effective for teenagers may not work well for adult learners or senior ...

Java Essentials Volume 2 provides structured pathway from Java fundamentals to advanced application development ...

Overview AI-powered streaming platforms analyze viewing habits, mood, and interaction patterns to efficiently suggest highly ...

Abstract: Preference-based Reinforcement Learning (PBRL) relies on the efficient collection and use of preference data to train accurate reward functions, enabling agents to learn directly from human ...

In a scenario where fame is given preference over family, the Akkineni family is a breath of fresh air with their humble, changing father-son relation.

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 ...