Friedrich-Alexander-Universität Erlangen
Lehrstuhl für Mustererkennung
Martensstraße 3
91058 Erlangen

Seminar Deep Learning Theory & Applications [SemDL]

Summary
Deep Neural Networks or so-called deep learning has attracted significant attention in the recent years. They have had a transformative influence on Natural Language Processing (NLP) and Artificial Intelligence (AI), with numerous success stories recent claims of superhuman learning performance in certain tasks. According to Young et al. (2017), more than 70% of the papers presented at recent NLP conferences made use of deep learning techniques. Interestingly, the concept of Neural Networks inspired researchers already over generations since Minky's famous book (cf. http://en.wikipedia.org/wiki/Society_of_Mind ). Yet again, this technology brings researchers to the believe that Neural Networks will eventually be able to learn everything (cf. http://www.ted.com/talks/jeremy_howard_the_wonderful_and_terrifying_implications_of_computers_that_can_learn ). This year's main topic is: „Social Bots: Danger or Myth?".

Dates & Rooms:
Wednesday, 10:15 - 11:45; Room: 01.019


Lecturer
Evert, Stefan
Christlein, Vincent
Kosti, Ronak