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Despite the high number of investments for data-based models in the expansion of Industry 4.0, too little effort has been made to ensure the maintenance of those models. In a data-streaming environment, data-based models are subject to concept drifts. A co ...
Graphs offer a simple yet meaningful representation of relationships between data. Thisrepresentation is often used in machine learning algorithms in order to incorporate structuralor geometric information about data. However, it can also be used in an inv ...
The present article proposes a methodology to consider the uncertainty intrinsic to data-based models when comparing their performance. The goal is to provide a quantification of the variability of this type of models due to the random nature of the calibr ...
This thesis proposes to address the well-know database integration problem with a new method that combines functionality from database conceptual modeling techniques with functionality from logic-based reasoners. We elaborate on a hybrid - modeling+validat ...
Modeling in neuroscience occurs at the intersection of different points of view and approaches. Typically, hypothesis-driven modeling brings a question into focus so that a model is constructed to investigate a specific hypothesis about how the system work ...
[Context] IT modelers create models to communicate their conceptualization of an organization and to facilitate the collaboration between business and IT people. The story they convey in their models is how the corporate IT systems fulfill the business peo ...
As the number of sensors that pervade our lives increases (e.g., environmental sensors, phone sensors, etc.), the efficient management of massive amount of sensor data is becoming increasingly important. The infinite nature of sensor data poses a serious chal ...
Computational models of biological systems aim at accurately simulating in vivo phenomena. They have become a very powerful tool enabling scientists to study complex behavior. A side effect of their success Unfortunately exists and is observed as an increa ...
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Object-centric learning has gained significant attention over the last years as it can serve as a powerful tool to analyze complex scenes as a composition of simpler entities. Well-established tasks in computer vision, such as object detection or instance ...
In this paper we consider distributed K-Nearest Neighbor (KNN) search and range query processing in high dimensional data. Our approach is based on Locality Sensitive Hashing (LSH) which has proven very efficient in answering KNN queries in centralized set ...
