Reviewing the latest research in machine learning, intelligent systems, systems and software engineering. Your lecturers are Prof. Dr. Nils Bertschinger, Prof. Dr. Matthias Kaschube and Prof. Dr. Visvanathan Ramesh.
General
Bachelor’s students are required to give a presentation only, Master’s also need to hand in a report about their topic (~ 5-10 pages), weighting for grade 50/50. Presentations will be at least 30 minutes plus discussion with the class. Course language is english. We will meet every week and presence is mandatory. Either choose one of the topics below and search for literature for yourself (papers, book-chapters, etc.), or choose a paper from here or request one from any professor above. You have to register with us until April, 27th. Everyone that is on our list until that date will be set for the course and given to the examination office.
TODO: Register AND select your topic until April, 27th
Dates
04.05. – Chutipong Bruhns – Perceptron
11.05. – Nicole Parrandier EM – Algorithms
18.05. – Wolfgang Stammer – Bayesian interpretation of NN
25.05. – Andy Grimm – Random Forest
01.06. – Fatime Bagheri – Self organizing maps
08.06. – Justine Smyzek – TBD
15.06. – Julian Kiling – TBD
22.06. – Rainer Killinger – Natural language processing
29.06. – Lars Petersen – Deep Learning
06.07. – Florian Stein – TBD
13.07. – Prof. Dr. Bertschinger – Neural Networks and Gaussian Processes
Topics
Classic algorithms ( Prof. Bertschinger, Prof. Kaschube )
- MCMC
- Gibbs sampling
- slice sampling
- EM algorithm
- Variational Bayes
- Optimization
Applications in economics and finance ( Prof. Bertschinger )
- VAR (Vector auto regression)
- asset pairing
- stochastic volatility
Neural networks ( Prof. Bertschinger, Prof. Kaschube, Prof. Ramesh )
- Bayesian interpretations
- Deep learning
- Backpropagation
Vision applications / image analysis ( Prof. Ramesh )
Neural data analysis ( Prof. Kaschube )
Software plattforms (Tensor flow, Torch, Theano, Caffee, Stan etc.) ( Prof. Ramesh )
Classification ( Prof. Bertschinger, Prof. Kaschube, Prof. Ramesh )
- Perceptron
- Support vector machines (SVM)
- Random forests
- Logistic regression