Abstract Computational language models (LMs), most notably exemplified by the widespread success of OpenAI's ChatGPT chatbot, show impressive performance on a wide range of linguistic tasks, thus providing cognitive science and linguistics with a computational working model to empirically study different...
Machine learning has become prevalent in transforming diverse aspects of our daily lives through intelligent digital solutions. Advanced disease diagnosis, autonomous vehicular systems, and automated threat detection and triage are some prominent use cases. Furthermore, the increasing use of machine learning...
Machine Learning algorithms are mainly divided into four categories: Supervised learning, Unsupervised learning, Semi-supervised learning, and Reinforcement learning [75], as shown in Fig.2. In the following, we briefly discuss each type of learning technique with the scope of their applicability to ...
Abstract Fano varieties are basic building blocks in geometry – they are ‘atomic pieces’ of mathematical shapes. Recent progress in the classification of Fano varieties involves analysing an invariant called the quantum period. This is a sequence of integers which gives a numerical fingerprint for ...
While machine learning may seem abstract at first, it can be expressed and understood in plain terms. Many of the tenets and frameworks for machine learning are based in mathematical operations that are likely familiar to any scientist or engineer, but applied in new ways. In this section, we...
In this section, we will take a closer look at some of the more common hybrid fields of study: semi-supervised, self-supervised, and multi-instance learning. 4. Semi-Supervised Learning Semi-supervised learningis supervised learning where the training data contains very few labeled examples and ...
Abstract The teaching of machine learning is now considered essential and relevant in schools globally. Despite the ongoing discourse and increased research in the emerging field, teachers' conceptions of machine learning remain under-researched. This study aims at filling the gap by describing the ...
Abstract Background Brucellosis is a common zoonotic infectious disease in China. This study aimed to investigate the incidence trends of brucellosis in China, construct an optimal prediction model, and analyze the driving role of climatic factors for human brucellosis. Methods Using brucellosis ...
Abstract Machine learning algorithms based on parametrized quantum circuits are prime candidates for near-term applications on noisy quantum computers. In this direction, various types of quantum machine learning models have been introduced and studied extensively. Yet, our understanding of how these ...
Abstract Evolutionary computation, for example, particle swarm optimization, has impressive achievements in solving complex problems in science and industry; however, an important open problem in evolutionary computation is that there is no theoretical guarantee of reaching the global optimum and general re...