Zuteilung der Seminarthemen

Die folgende Zuteilung der Seminarthemen ergab sich aufgrund des Themenbasars am 3. April:

Online Statistiken

• Elias K.: Finding Frequent Items in Data Streams
• Christian M.: Approximate Frequency Counts over Data Streams
• Benjamin B.: A simpler and more Efficient Deterministic Scheme for Finding Frequent Items over Sliding Windows
• Kolja W.: Space-Efficient Online Computation of Quantile Summaries
• Damiel S.: Mining Frequent Itemsets in a Stream

Klassifikation

• Till H.: Naive Bayes for Text Classification with Unbalanced Classes
• Lukas P.: Fast Kernel Classifiers with Online and Active Learning
• Stefan R.: Large-Scale Machine Learning with Stochastic Gradient Descent

Clustering

• Jan G.: A Framework for Clustering Evolving Data Streams
• Christian C.: Stream-KM++: A Clustering Algorithm for Data Streams

Ausreißer-Erkennung

• Fabian W.: Continuous Monitoring of Distance-Based Outliers over Data Streams
• Hendrik F.: Detecting Outliers on Arbitrary Data Streams using Anytime Approaches
• Tim H.: Incremental Local Outlier Detection for Data Streams
• Markus F.: Adaptive Concept Drift Detection