Seminar: Pattern Analysis and Machine Intelligence (WS 17/18)

Seminar Pattern Analysis and Machine Intelligence (Winter  Semester 2017)

Reviewing the latest research in machine learning and intelligent systems. Your lecturers are Prof. Dr. Nils Bertschinger, Prof. Dr. Matthias Kaschube and Prof. Dr. Visvanathan Ramesh.

Time: Thursday, 8:00 am c.t.  SR 9

For any questions please contact us teaching@ccc.cs.uni-frankfurt.de

General

Bachelors students are required to give a presentation only, Masters also need to hand in a report about their topic (~ 5-10 pages), weighting for grade 50/50. Presentations will be around 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. Registration is mandatory and will be passed to the examination-office.

Presentation Dates and Schedule

  • 19.10.2017 – Seminar Overview, Logistics, Themes of Papers
  • 26.10.2017 – no seminar, paper selection and review

Seminar Schedule:

Datum Betreuer anrede vorname nachname Thema
11/16/2017 Ramesh Herr Felix Schatten On the Origin of Deep Learning
11/16/17 Ramesh Herr Sebastian Voinea On the Origin of Deep Learning
11/23/17 Ramesh Frau Madeleine Henkel 50 years of Data Science
11/23/17 Ramesh Herr Philipp Scholl 50 years of Data Science
12/7/17 Bertschinger Herr Andreas Haupt Deep Symmetry Networks
12/7/17 Bertschinger Herr Arvin Matic On Random Weights and Unsupervised Feature Learning
11/30/17 Bertschinger Frau Yana Ezhkina Bayesian analysis of GARCH and stochastic volatility: modeling leverage, jumps and heavy-tails for financial time series
12/14/17 Bertschinger Herr Boris Hähnlein Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
12/14/17 Bertschinger Herr Fabian Knöller Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images
12/21/17 Bertschinger Frau Katarzyna Kujawa Model-based machine learning
12/21/17 Bertschinger Herr Nikias Heß Stan: A probabilistic programming language for Bayesian inference and Optimization
1/11/18 Ramesh Herr Moritz Faust On Cognitive Dynamic Systems: Cognitive Neuroscience and Engineering Learning From Each Other
1/18/18 Kaschube Herr Christopher Posselt Deep convolutional models improve predictions of macaque V1 responses to natural images
1/18/18 Kaschube Herr Eike Henrich Deep convolutional models improve predictions of macaque V1 responses to natural images
1/25/18 Kaschube Herr Bashir Lawand Synthesising Dynamic Textures using Convolutional Neural Networks
1/25/18 Kaschube Herr Julius Taylor Texture Synthesis using Convolutional Neural Networks
2/1/18 Kaschube/Ramesh Frau Yu Yi Yang Representation learning
2/1/18 Kaschube/Ramesh Herr Sitong Yu A Taxonomy of Deep Convolutional Neural Nets for Computer Vision

Topics and Papers:

Link to Papers from Prof. Ramesh (password protected, password will be sent by email to registrants)