In the first case study banking financial data and in the second one the data of the empirical study into Estonian concepts of emotion are analyzed. In the thesis the basis of the theories of knowledge and concepts are reviewed. The two-dimensional topological representation of data on...
Considerable advances have been made in the field of machine learning (ML), with deep neural networks (DNNs)1in particular achieving impressive performances on a multitude of domains2,3,4. However, the reasoning of these highly complex and nonlinear DNNs is generally not obvious5,6, and, as ...
Continuous-depth neural networks, such as the Neural Ordinary Differential Equations (NODEs), have aroused a great deal of interest from the machine learning and data science communities in recent years. There are many examples of work in this...
Concepts, as the basic units of thought underlying human intelligence and communication, may play a fundamental role when integrating the results from the two fields in terms of information and knowledge coding, representation, communication, and processing. While cognitive informatics focuses on ...
In Proc. 35th International Conference on Machine Learning 50–59 (ICML, 2018). Chen, X. et al. InfoGAN: interpretable representation learning by information maximizing generative adversarial nets. In Proc. 30th Conference on Advances in Neural Information Processing Systems 2172–2180 (NeurIPS, 2016...
How can models be stored in a repository with a compact representation? It has to deal with the trade-off between memory requirements and the loss of details of the clusters. How recurring concepts can be identified in unsupervised learning. Concerning concept recurrence, what difference does it ...
Proper visual representation of data is also very relevant to user's understanding - visualization is often utilised in machine learning since it shifts the balance between perception and cognition to take fuller advantage of the brain's abilities. In this paper we review visualisation in incremental...
In this way, the whole network learns to optimize the localization task. Brahmbhatt, Gu, Kim, Hays, and Kautz (2018) propose a mapping model based on a regression neural network, which enables learning a data-driven map representation. Furthermore, the proposed network can be updated with ...
The potential contribution of machine learning in this situation has not been fully evaluated. The objective of this study was to develop and evaluate machine learning models using routine clinical and laboratory data to improve the performance of RT-PCR and chest-CT for COVID-19 diagnosis among ...
Concept-based information retrieval and knowledge representation are in need of a theory of concepts and semantic relations. Guidelines for the constructio... WG Stock - 《Journal of the American Society for Information Science & Technology》 被引量: 54发表: 2014年 Generalizing the Structure of Exp...