January 2021

31 to 36 of 49

16JAN 2021
Lecture Notes in Pattern Recognition
Lecture Notes in Pattern Recognition: Episode 26 – Mercer’s Theorem and the Kernel SVM
These are the lecture notes for FAU’s YouTube Lecture “Pattern Recognition“. This is a full transcript of the lecture video & matching slides. We hope, you enjoy this as much as the videos. Of course, this transcript was created with deep learning techniques largely automatically and only minor manual modifications were performed. Try it yourself! If you […]
Read more about Lecture Notes in Pattern Recognition: Episode 26 – Mercer’s Theorem and the Kernel SVM
16JAN 2021
Lecture Notes in Pattern Recognition
Lecture Notes in Pattern Recognition: Episode 25 – Support Vector Machines – Optimization
These are the lecture notes for FAU’s YouTube Lecture “Pattern Recognition“. This is a full transcript of the lecture video & matching slides. We hope, you enjoy this as much as the videos. Of course, this transcript was created with deep learning techniques largely automatically and only minor manual modifications were performed. Try it yourself! If you […]
Read more about Lecture Notes in Pattern Recognition: Episode 25 – Support Vector Machines – Optimization
15JAN 2021
News
Invited Talk by Matthias Niessner – Jan 21st 2021, 12h CET
It is a great pleasure to announce a new guest presentation by Matthias Niessner from TU Munich! Title: 3D Semantic Scene UnderstandingDate: 21st of January, 2021, 12h, noon CETLocation: https://fau.zoom.us/j/93218875951?pwd=TXdVdi9nVTVRa09ya1V2aWk5Z0d1UT09 Abstract: In recent years, commodity 3D sensors, such as the Microsoft Kinect, have become easily and widely available. These advances in sensing technology have inspired significant […]It is a great pleasure to announce a new guest presentation by Matthias Niessner from TU Munich! Title: 3D Semantic Scene UnderstandingDate: 21st of January, 2021, 12h, noon CETLocation: https://fau.zoom.us/j/93218875951?pwd=TXdVdi9nVTVRa09ya1V2aWk5Z0d1UT09 Abstract: In recent years, commodity 3D sensors, such as the Microsoft Kinect, have become easily and widely available. These advances in sensing technology have inspired significant […]
Read more about Invited Talk by Matthias Niessner – Jan 21st 2021, 12h CET
15JAN 2021
Deep Learning WS 20/21
Watch now: Deep Learning: Reinforcement Learning – Part 5 (WS 20/21)
In the last video on reinforcement learning, we look into the deep reinforcement learning techniques. We start looking into how Deep Mind beat Atari Games and in particular breakout. Furthermore, we look into the technology behind AlphaGo and AlphaGoZero to play Go, Chess, and Shogi on world-class level. Watch on:FAU TVFAU TV (no memes)YouTube Read […]
Read more about Watch now: Deep Learning: Reinforcement Learning – Part 5 (WS 20/21)
14JAN 2021
Pattern Recognition WS 20/21
Watch now: Pattern Recognition: Episode 32 – Independent Component Analysis – Introduction (WS 20/21)
In this video, we introduce the concept of the independent component analysis. Watch on:FAU TVYouTube
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14JAN 2021
Deep Learning WS 20/21
Watch now: Deep Learning: Reinforcement Learning – Part 4 (WS 20/21)
This video discusses several other solution approaches to learning games such as Monte Carlo Techniques, Temporal Difference Learning, Q Learning, and learning universal function approximators for reinforcement learning using the policy gradient. Watch on:FAU TVFAU TV (no memes)YouTube Read the Transcript (Summer 2020) at:LMETowards Data Science
Read more about Watch now: Deep Learning: Reinforcement Learning – Part 4 (WS 20/21)