Department of Computer Science | Institute of Theoretical Computer Science | CADMO

Theory of Combinatorial Algorithms

Prof. Emo Welzl and Prof. Bernd Gärtner

Mittagsseminar (in cooperation with A. Steger, D. Steurer and B. Sudakov)

Mittagsseminar Talk Information

Date and Time: Thursday, May 10, 2012, 12:15 pm

Duration: 30 minutes

Location: OAT S15/S16/S17

Speaker: Stephan Kollmann

Topology Learning in Spiking Recurrent Competitive Networks (Master thesis)

Recently it has been shown that recurrent neural networks with initially random connections and weights can learn the topology of an external input using a rate based neuron model and a Hebbian learning rule. However it was not clear whether these results can be reproduced in a more biologically plausible setting. We show that similar results can also be achieved using a spiking neuron model and a STDP (Spike Timing Dependent Plasticity) learning rule that is based on triplets of spikes (it has been shown that experimental data can be explained well using such a rule). We further analyze the trained network's ability to exhibit certain soft-winner-take-all behavior, namely signal restoration, winner selection and cue integration.

Upcoming talks     |     All previous talks     |     Talks by speaker     |     Upcoming talks in iCal format (beta version!)

Previous talks by year:   2024  2023  2022  2021  2020  2019  2018  2017  2016  2015  2014  2013  2012  2011  2010  2009  2008  2007  2006  2005  2004  2003  2002  2001  2000  1999  1998  1997  1996  

Information for students and suggested topics for student talks

Automatic MiSe System Software Version 1.4803M   |   admin login