Abstract: In the field of single objective optimization algorithms, learned evolutionary algorithms have achieved success in obtaining better performance than human-designed strategies. However, these ...
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, ...
AI improves renewable energy forecasting accuracy by up to 33%, helping grid operators better integrate solar and wind resources. Predictive maintenance powered by AI reduces equipment downtime by ...
Deep neural networks (DNNs), which power modern artificial intelligence (AI) models, are machine learning systems that learn hidden patterns from various types of data, be it images, audio or text, to ...
Abstract: This paper presents LLM2TEA, a Large Language Model (LLM) driven MultiTask Evolutionary Algorithm, representing the first agentic AI designer of its kind operating with generative ...
They’re harnessing it to help directors prepare, debate, and decide. by Stanislav Shekshnia and Valery Yakubovich In 2014 Hong Kong–based Deep Knowledge Ventures formally appointed an algorithm to its ...
Facebook's vice president of product, Jagjit Chawla, talks about how the platform treats AI-generated content and how you can see less of it. Katelyn is a writer with CNET covering artificial ...
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