In a world where self-driving robotaxis glide through major city streets without drivers behind the wheel and delivery drones ...
Developers are increasingly relying on large language models (LLMs) for everyday computing tasks such as fixing bugs, ...
Combinatorial optimization problems are often encountered in real-world applications, including logistics, scheduling and ...
Abstract: Data imbalance in Machine Learning refers to an unequal distribution of classes within a dataset. This issue is encountered mostly in classification tasks in which the distribution of ...
Abstract: A machine-learning-assisted optimization (MLAO) method for antenna geometry design (AGD) (MLAO-AGD) is proposed. By combining machine learning (ML) methods, including a convolutional neural ...
As energy companies push AI deeper into industrial operations, success increasingly depends on governance, trusted data, and ...
As energy companies push AI deeper into industrial operations, success increasingly depends on governance, trusted data, and ...