机器学习的求解过程可以看作是在假设空间中搜索一个具有强泛化能力和高鲁棒性的学习模型,
而在假设空间中寻找合适模型的过程是较为困难的. 然而, 集成学习作为一类组合优化的学习 …

Informatics paradigms for brain and mental health research have seen significant advances
in recent years. These developments can largely be attributed to the emergence of new …

Cervical cancer is the fourth most common cancer among women, and cytopathological
images are often used to screen for this cancer. However, manual examination is very …

Environmental variability is still a major challenge in structural health monitoring. Due to the
similarity of changes caused by environmental variations to damage, false positive and false …

Property valuation contributes significantly to market economic activities, while it has been
continuously questioned on its low transparency, inaccuracy and inefficiency. With Big Data …

From the perspective of clinical decision-making in a Medical IoT-based healthcare system,
achieving effective and efficient analysis of long-term health data for supporting wise clinical …

Temporal data clustering can provide underpinning techniques for the discovery of intrinsic
structures, which proved important in condensing or summarizing information demanded in …

One of the main challenges in traumatic brain injury (TBI) patients is to achieve an early and
definite prognosis. Despite the recent development of algorithms based on artificial …

Skin cancer poses a significant healthcare challenge, requiring precise and prompt
diagnosis for effective treatment. While recent advances in deep learning have dramatically …

The process of solving machine learning can be regarded as searching for a learning model
with strong generalization ability and high robustness in the hypothesis space, and it is more …