Active Learning for experimental exploration
Analyse von Zeitreihen-Kompressionsmethoden am Beispiel von Google N-Grams
Approximating an Ngram Corpus with Probabilistic Methods
Auswahl von SAT Instanzen zur Evaluation von Solvern
Batch query strategies for one-class active learning
Canonical Monte Carlo Dependency Estimation
Collective Entity Matching for Linking Structures in Attributed Material Graphs
Density-Based Outlier Detection Benchmark on Synthetic Data
Detecting Outlying Time-Series with Global Alignment Kernels
Developing a Database Application to Compare the Google Books Ngram Corpus to German News Corpora
Developing a Framework for Mining Temporal Data from Twitter as Basis for Time-Series Correlation Analysis
Development and evaluation of efficient kNN search of time series subsequences using the example of the Google Ngram data set
Development of an Active Learning Approach for One Class Classiﬁcation using Bayesian Uncertainty
Efficient Reduction of Energy Time Series
Efficient Training of Graph Neural Networks for Dynamic Phenomena (Proposal)
Entwicklung einer Methode zum Vergleich mehrsprachiger und zeitabhängiger Textkorpora am Beispiel des Google Books Ngram Datensatzes
Implementation and Evaluation of CHQL Operators in Relational Database Systems
Improving Document Information Extraction with efficient Pre-Training
Information Content of Targeted Disturbances in the Electrical Grid
Informationsbedürfnisse zur Untersuchung der Begriffsgeschichte
Injection Molding Simulation based on Graph Neural Networks
Local Outlier Factor for Feature‐evolving Data Streams
Modeling Dynamic Systems using Slope Constraints: An Application Analysis of Gas Turbines
Monitoring Complex Systems with Domain Knowledge: Adapting Contextual Bandits to Tracing Data
Neural-Based Outlier Detection in Data Streams
On the Converge of Monte Carlo Dependency Estimators
Patient Rule Induction Method with Active Learning
Predictability of Classiﬁcation Performance Measures with Meta-Learning
Predicting System Dependencies from Tracing Data Instead of Computing Them
Query Synthesis in One-Class Active Learning
Reinforcement Learning for Solving the Knight’s Tour Problem
Review of data efficient dependency estimation
Review of dependency estimation with focus on data efficiency
Skalierung der SVDD für große Datenmengen
Standardized Real-World Change Detection Data
State of the Art: Multi Actor Behaviour and Dataflow Modelling for Dynamic Privacy
Statistical Generation of High-Dimensional Data Streams with Complex Dependencies
Subspace Generative Adversarial Learning for Unsupervised Outlier Detection
Surrogate Model Based Process Parameters Optimization of Textile Forming
Surrogate models for crystal plasticity - predicting stress, strain and dislocation density over time
Tabular Data Augmentation for Mixed Data
Theory-Guided Data Science for Lithium-Ion Battery Modeling
Trend Monitoring on Twitter Streams with Semantic Change Analysis
Tuning of Explainable Artificial Intelligence (XAI) tools in the field of text analysis
Untersuchung der Auswirkungen von Messdatenverschleierung auf Disaggregations-Qualität
Untersuchung des Trade-Offs zwischen Privacy und Forecasting-Qualität
User-centric Outlier Detection on Energy Data
Wichtigkeit von Merkmalen für die Klassifikation von SAT-Instanzen (Proposal)