Abstract Decision Trees (DTs) are predictive models in supervised learning, known not only
for their unquestionable utility in a wide range of applications but also for their interpretability …

Recent years have witnessed promising artificial intelligence (AI) applications in many
disciplines, including optics, engineering, medicine, economics, and education. In particular …

Page 1 不确定理论与优化丛书 Uncertainty Theory and Optimization Series 不确定规划及应用
Uncertain Programming with Applications 刘宝碇赵瑞清王纲著 Liu Baoding Zhao Ruiqing …

Recent advances in deep neural networks (DNNs) have mainly focused on innovations in
network architecture and loss function. In this paper, we introduce a flexible high-order …

Deep neural networks (DNNs) have achieved great success in many applications. The
architectures of DNNs play a crucial role in their performance, which is usually manually …

Large Language Models (LLMs) excel in various tasks, but they rely on carefully crafted
prompts that often demand substantial human effort. To automate this process, in this paper …

During learning, the brain modifies synapses to improve behaviour. In the cortex, synapses
are embedded within multilayered networks, making it difficult to determine the effect of an …

Providing natural language instructions in prompts is a useful new paradigm for improving
task performance of large language models in a zero-shot setting. Recent work has aimed to …

Recent years have seen an increasing interest in Demand Response (DR) as a means to
provide flexibility, and hence improve the reliability of energy systems in a cost-effective way …

Artificial intelligence has been applied in wildfire science and management since the 1990s,
with early applications including neural networks and expert systems. Since then, the field …