Google has demonstrated a 13,000 times speedup for the Quantum Echoes algorithm using its Willow quantum chip. The feat is repeatable, according to the company, and it paves the way toward real-world ...
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, ...
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 ...
Large language models (LLMs) leverage unsupervised learning to capture statistical patterns within vast amounts of text data. At the core of these models lies the Transformer architecture, which ...
1 State Key Laboratory of Intelligent Mining Equipment Technology, Taiyuan, China 2 School of Computer Science and Technology, Anhui University, Hefei, China In the manufacturing process of electric ...
ABSTRACT: In this study, we aim to examine the dynamics of diseases by employing both voluntary and forced control strategies backed by evolutionary game theory (EGT). The impact of quarantine is ...
Abstract: Large-scale constrained multiobjective optimization problems (LSCMOPs) exist widely in science and technology. LSCMOPs pose great challenges to algorithms due to the need to optimize ...
A new study by researchers at the Max Planck Institute for Evolutionary Biology (MPI-EB) sheds fresh light on one of the most debated concepts in biology: evolvability. The work provides the first ...
Abstract: In the domain of multi-objective optimization, evolutionary algorithms are distinguished by their capability to generate a diverse population of solutions that navigate the trade-offs ...
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