The minimization of the loss function is of paramount importance in deep neural networks. On the other hand, many popular optimization algorithms have been shown to correspond to some evolution equation of gradient flow type. Inspired by the numerical schemes used for general evolution equations we introduce a second order stochastic Runge Kutta me...
MoreAir is a low-cost and agile urban air pollution monitoring system. This paper describes the methodology used in the development of this system along with some preliminary data analysis results. A key feature of MoreAir is its innovative sensor deployment strategy which is based on mobile and nomadic sensors as well as on medical data collected ...
Machine Learning (ML) applications are becoming increasingly valuable due to the rise of IoT technologies. That is, sensors continuously gather data from different domains and make them available to ML for learning its models. This provides profound insights into the data and enables predictions about future trends. While ML has many advantages, it...
There are abundant cases for using Topological Data Analysis (TDA) in a learning context, but robust topological information commonly comes in the form of a set of persistence diagrams, objects that by nature are uneasy to affix to a generic machine learning framework. We introduce a vectorisation method for diagrams that allows to collect informat...
Since building a machine learning model costs a lot while following 9 stages, the automated machine learning model creation became a crucial role in a large-scale context. At the same time, a monitoring system became an essential factor for machine learning models. This thesis presents the monitoring system for machine learning models at ING in an ...
Recently, indoor modeling has gained increased attention thanks to the immense need for realizing efficient indoor location-based services. Indoor environments de facto differ from outdoor spaces in two aspects: spaces are smaller and there are many structural objects such as walls, doors, and furniture. To model the indoor environments in a proper...
As the level of greenhouse gas emissions increases, so does the importance of the energy performance of buildings (EPB). One of the main factors to measure EPB is a structure&rsquo / s heating load (HL) and cooling load (CL). HLs and CLs depend on several variables, such as relative compactness, surface area, wall area, roof area, overall height, o...
Memristor-based, non-von-Neumann architectures performing tensor operations directly in memory are a promising approach to address the ever-increasing demand for energy-efficient, high-throughput hardware accelerators for Machine Learning (ML) inference. A major challenge for the programmability and exploitation of such Computing-In-Memory (CIM) ar...
One interesting part of the application of human activity recognition is sports motion recognition and classification. In recent years, many commercial wearable devices have been used for recording and supervising motion data information during sports. However, their claimed high-accuracy results but motion recognition and classification method hav...
In studies of wind plant designs, wake dynamics are of great interests as wakes affect downstream turbine loading that impacts wind plant efficiency. Recent developments of Tensor Basis Decision Tree (TBDT) based machine learning (ML) models in reconstructing the turbulence anisotropy fields of simple flow cases prompt the motivation in applying su...
