05: Maschinelles Lernen 2 - Fortgeschrittene Verfahren, Vorlesung, SS 2017, 07.07.2017
Author
Editor
Participating institute
Institut für Anthropomatik und Robotik (IAR)
Genre
Description
- 0:00:00 Starten
- 0:00:21 Motivation Video: SPAUN
- 0:03:27 Overview
- 0:04:27 Neurons anatomy
- 0:05:35 Neurons in action
- 0:07:42 Modelling Neurons
- 0:09:04 Synaptic plasticity
- 0:11:41 Coding information
- 0:14:06 Why not backpropagation in spiking networks?
- 0:17:05 Os backpropagation biologically possible
- 0:21:43 Synaptic plasticity as learning
- 0:23:41 Different types of long-term synaptic plasticity
- 0:24:18 Formalization of precise spiketime plasticity rules
- 0:27:23 Example: Hebbian and anti-hebbian learning rules
- 0:28:55 Formalization of rate-based plasticity rules
- 0:32:56 Formalization of reward-based plasticity rules
- 0:34:50 Other neuromodulators
- 0:36:32 Structural plasticity - rewiring synapses
- 0:40:14 Unsupervised learning with STDP
- 0:42:43 Supervised learning with STDP - Associative learning
- 0:44:18 SPORE - Synaptic Plasticity with Online Reinforcement learning
- 0:45:45 SPORE in action - Binary classification
- 0:47:08 Spiking Networks as kernel methods
- 0:48:44 Linear reression on rates - Neural Engineeering Framework
- 0:52:13 Regression on Post-Synaptic Potentials - Liquid State Machines
- 0:54:07 Liquid State Machines in real life
- 0:56:21 Neuromorphic chips - spiking network
- 1:01:52 Neuromorphic sensors -Silicon retina (DVS)
- 1:03:54 Short-term visual prediction of address events
- 1:04:36 Connecting robots to spiking networks
- 1:05:41 Grasping motions with spiking networks
- 1:06:37 End-to-end robot control - Braitenberg vehicles
- 1:09:44 mBuilding Braitenberg vehicles in simulation
- 1:11:53 Where to o next?
Duration (hh:mm:ss)
01:12:49
Series
Maschinelles Lernen 2 - Fortgeschrittene Verfahren, Vorlesung, SS 2017
Published on
11.07.2017
Subject area
License
| Resolution | 1280 x 720 Pixel |
| Aspect ratio | 16:9 |
| Audio bitrate | 112661 bps |
| Audio channels | 2 |
| Audio Codec | aac |
| Audio Sample Rate | 48000 Hz |
| Total Bitrate | 917900 bps |
| Color Space | yuv420p |
| Container | mov,mp4,m4a,3gp,3g2,mj2 |
| Media Type | video/mp4 |
| Duration | 4370 s |
| Filename | DIVA-2017-413_hd.mp4 |
| File Size | 4.096 byte |
| Frame Rate | 25 |
| Video Bitrate | 799143 bps |
| Video Codec | h264 |
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Maschinelles Lernen 2 - Fortgeschrittene Verfahren, Vorlesung, SS 2017
Episodes 1-8
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