Machine learning interview questions now focus on both theory and real-world applications.Understanding basics like overfitting, bias, and regres ...

New research proposes a unified theory of brain function based on criticality—a state where the brain teeters between order ...

The concept analysis (12) made it possible to identify and describe the definitions of the concept of Meaningful Learning, according to the Meaningful Learning Theory (4), in the area of Nursing. The ...

Our brains may work best when teetering on the edge of chaos. A new theory suggests that criticality a sweet spot between order and randomness is the secret to learning, memory, and adaptability. When ...

The multi-agent system is the optimal solution to complex intelligent problems. In accordance with the game theory, the concept of loyalty is introduced to analyze the relationship between agents' ...

In a new paper with implications for preventing Alzheimer's disease and other neurological disorders, Keith Hengen, an associate professor of biology in Arts & Sciences at Washington University in St.

Based on these considerations, determining the optimal sequence of these learning methods in practical motor learning situations is essential for maximizing the benefits of both approaches—enhancing ...

We introduce a state-interaction approach for computing g-matrices within time-dependent density functional theory (TDDFT) and the Tamm–Dancoff approximation (TDA), applied here for the first time.

This article describes a novel concept to optimize manufacturing systems distributively through data-based learning. We propose a game-theoretic (GT) learning set-up that is incorporated with ...

Numerical evaluation of such optimal stochastic control theory in production and inventory model of fixed or constant demand rates with its sensitivity effects were illustrated.