Understanding the mechanism of how neural networks learn features from data is a fundamental problem in machine learning. Our work explicitly connects the mechanism of neural feature learning to a ...

In a paper posted last week by Google's DeepMind unit, researchers Chengrun Yang and team created a program called OPRO that makes large language models try different ...

Artificial neural networks are very time consuming and energy intensive to train, especially when increasing the size of the neural network in an attempt to improve the performance. In this paper, we ...

Abstract: By utilizing a neural-network-based adaptive critic mechanism, the optimal tracking control problem is investigated for nonlinear continuous-time (CT ...

Deep learning networks have been trained to recognize speech, caption photographs, and translate text between languages at high levels of performance. Although applications of deep learning networks ...

Worse-case analysis takes a “Murphy’s Law” approach to algorithm analysis, which is too crude to give meaningful algorithmic guidance for many important problems, including linear programming, ...

What is the effect of programming languages on software quality? This question has been a topic of much debate for a very long time. In this study, we gather a very large data set from GitHub (728 ...

We provide Ising formulations for many NP-complete and NP-hard problems, including all of Karp's 21 NP-complete problems. This collects and extends mappings to the Ising model from partitioning, ...