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Theses in Progress
Sovit Agrawal
Unsupervised Detection of Anomalies in Distributed System Logs
Nedelkoski [1]
Trieu Minh Bui
Implementierung eines WEKA-Plugins am Beispiel einer graphen-basierten Feature Selection mit maximalen Cliquen
Styp-Rekowski [2]
Luk Bjarne Burchard
Efficient Imaging of Temporal online Networks under strict Accesss Constraints
Kao [3]
Wladimir Gaus
Adaptive Scheduling of Distributed Stream Processing in heterogeneous IoT environments
Thamsen [4]
Kyra Kasz
Autoencoder-based Anomaly Detection for combinded Sewage Overflow Monitoring
Lorenz [5]
Abdallah Kadour
Design of an Integration Framework for eHealth-Services
Kao [6]
Syed Jafer Raza Naqvi
Multi-Source Metric Data Collection and Correlation in Public Cloud Infrastructures
Acker [7]
Eva Nguyen
The Potentials of AIOPs for large Companies - a Market Analysis Approach
Schmidt [8]
Harald Ott
Infrastructure-Agnostic Anomaly Detection in Cloud Environments
Nedelkoski [9]
Marcin Ozimirski
Sink directed Routing for Wake-up Sensor Mesh Networks
Lorenz [10]
Ahmad Sabtain
Application of Neural Networks in Unsupervised Anomaly Detection from Time and Frequency Data of Rotating Machines
Styp-Rekowski [11]
Dominik Scheinert
Deep Metric Learning for Multivariate Time Series - A Graph Convolutional Neural Network Approach
Acker [12]
Phillip Stagnet
Erstellung und Umsetzung eines Konzeptes zur Konfiguration und Distribution verteilter containerbasierter Enterprise-Anwendungen
Kao [13]
Heye Vöcking
Bluestreak - Privacy aware User Segmentation for Online Advertisement using Linear Regression
Becker [14]
Tim Stahl
Using IoT Devices and hidden Markov Models to estimate Clogging of Street Inlets
Lorenz [15]
Philipp Wiesner
Simulation of Energy Consumption in Fog Computing Environments
Thamsen [16]
Christopher Woggon
Optimized Placement of Resource-Constrained Distributed Data Stream Operators
Gulenko [17]
Jessica Woods
Adaptive Checkpointing for Distributed Stream Processing
Thamsen [18]
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