Bacteriophage research stands at the crossroads of virology, genomics, and microbial ecology, with phages recognized as the ...
Social media algorithms driven by AI shape far more than what appears on our screens, including how we think, feel, and ...
Abstract: Over the past decades, extensive research has been conducted on adversarial attacks and defense mechanisms in deep learning, particularly in real-world applications such as autonomous ...
High-dimensional data often contain noisy and redundant features, posing challenges for accurate and efficient feature selection. To address this, a dynamic multitask learning framework is proposed, ...
The project aimed to develop a full stack of technologies to bring the practical advantages of quantum computing to industry in the near term Quantum computing is one of the frontiers of research and ...
ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...
A new evolutionary technique from Japan-based AI lab Sakana AI enables developers to augment the capabilities of AI models without costly training and fine-tuning processes. The technique, called ...
Mikel Hernaez receives funding from the Spanish Ministry of Science, Innovation and Universities, the government of Navarra, the EU Department of Defence, the Carlos III Health Institute and the ...
Abstract: Dynamic constrained multiobjective optimization problems (DCMOPs) are widely existed in real-world applications and emerged as a prominent research focus in the evolutionary computation ...
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