Lehr- und Forschungseinheit für Datenbanksysteme
print


Breadcrumb Navigation


Content

Deep Learning and Artificial Intelligence (WS 2019/20)

News

Organisation

  • Assistants: Sabrina Friedl
  • Required: Lecture "Machine Learning" or equivalent, Lecture "Knowledge Discovery in Databases I" or equivalent
  • Audience: The lecture is directed towards Master students in Mediainformatics, Bioinformatics,  Informatics, and Data Science

Final Exam

When: Wed, Feb 19 2020, 4 p.m. - 6 p.m. (16:00 -- 18:00 Uhr) sine tempore!>
Where: Main Building B 101
Registration: Uni2Work
Allowed aids: Two sheets of Din A4 paper with handwritten notes on both sides, calculator

Additional Exam

When: tbd
Where: tbd
Registration: tbd
Allowed aids: Two sheets of Din A4 paper with handwritten notes on both sides, calculator

Time and Locations

All times are c.t. (cum tempore)

Component When Where Starts at
Lecture Wed, 13.00 - 16.00 h Room S 004 (Schellingstr. 3) 16.10.2019
Tutorial 1 Mo, 14.00 - 16.00 h Room R 051 (Schellingstr. 3) 21.10.2019
Tutorial 2 Mo 16.00 - 18.00 h Room R 051 (Schellingstr. 3) 21.10.2019

Content

During the last decade the availability of large amounts of data and the strong increase in computing power allowed a renaissance of neural networks and advanced planning techniques for independent agents. Whereas the area of deep learning extended well established neural network technology to allow a whole new level of data transformation, modern reinforcement learning techniques yield the artificial backbone for intelligent assistant systems and autonomous vehicles.

The course starts with an introduction to neural networks and explains the developments that led to deep architectures. Furthermore, the course gives an introduction to advanced planning techniques and how they can be trained using deep neural networks and other machine learning technologies.

Course Schedule

Lecture Tutorial
Date Topic Date
16.10.2019 Introduction
Speaker: Sigurd Spieckermann
21.10.2019
23.10.2019 Basic Neural Networks
Speaker: Yinchong Yang
28.10.2019
30.10.2019 Training Neural Networks
Speaker: Sigurd Spieckermann
04.11.2019
06.11.2019 Deep Learning Tools
Speaker: Denis Krompass
11.11.2019
13.11.2019 Convolutional Neural Networks
Speaker: Denis Krompass
18.11.2019
20.11.2019 Recurrent Neural Networks
Speaker: Pankaj Gupta
25.11.2019
27.11.2019 Deep Learning and Uncertainty
Speaker: Florian Büttner
02.12.2019
04.12.2019 Representation and Distributional Learning
Speaker: Pankaj Gupta
09.12.2019
11.12.2019 Generative Models
Speaker: Yinchong Yang
16.12.2019
18.12.2019 Sequential Decision Problems and Autonomous Agents
Speaker: Matthias Schubert
07.01.2020
08.01.2020 Model-free Reinforcement Learning
Speaker: Matthias Schubert
13.01.2020
15.01.2020 Value Function Approximation
Speaker: Matthias Schubert
20.01.2020
22.01.2020 Policy Gradients and Actor Critic Learning
Speaker: Ma tthias Schubert
27.01.2020
29.01.2020 Knowledge Graphs in AI
Speaker: Volker Tresp
03.02.2020
05.02.2020 Q&A ----------------