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smu
lectures
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2024/05/29 15:07 kuzelon2 [Lecture 3 - Reinforcement Learning 3]
2024/05/20 15:11 zelezny [Literature]
2024/05/20 14:36 tothjan2
2024/05/20 14:35 tothjan2
2024/04/29 15:15 souregus
2024/04/22 15:03 souregus
2024/04/15 14:57 souregus [Lecture 8 - Natural Language Processing 2]
2024/04/08 10:29 souregus [Lecture 7 - Natural Language Processing 1]
2024/03/26 09:52 tothjan2 [Literature]
2024/03/25 15:51 kuzelon2 [Lecture 6 - Reinforcement Learning 6]
2024/03/18 15:00 kuzelon2 [Lecture 5 - Reinforcement Learning 5]
2024/03/18 14:57 kuzelon2 [Lecture 4 - Reinforcement Learning 4]
2024/03/18 14:57 kuzelon2 [Lecture 4 - Reinforcement Learning 4]
2024/03/18 14:54 kuzelon2 [Lecture 3 - Reinforcement Learning 3]
2024/03/11 15:59 kuzelon2 [Lecture 4 - Reinforcement Learning 4]
2024/03/04 14:47 kuzelon2 [Lecture 3 - Reinforcement Learning 3]
2024/02/26 15:02 kuzelon2 [Lecture 1 - Reinforcement Learning 1]
2024/02/26 15:01 kuzelon2 [Lecture 1 - Reinforcement Learning 1]
2024/02/26 14:49 kuzelon2 [Lecture 1 - Reinforcement Learning 1]
2024/02/26 14:45 kuzelon2 [Lecture 2 - Reinforcement Learning 2]
2024/02/16 15:13 souregus
2024/02/16 15:12 souregus [Lecture 7 - Natural Language Processing 1]
2024/02/16 14:07 kuzelon2
2024/02/09 10:14 external edit
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2024/05/29 15:07 kuzelon2 [Lecture 3 - Reinforcement Learning 3]
2024/05/20 15:11 zelezny [Literature]
2024/05/20 14:36 tothjan2
2024/05/20 14:35 tothjan2
2024/04/29 15:15 souregus
2024/04/22 15:03 souregus
2024/04/15 14:57 souregus [Lecture 8 - Natural Language Processing 2]
2024/04/08 10:29 souregus [Lecture 7 - Natural Language Processing 1]
2024/03/26 09:52 tothjan2 [Literature]
2024/03/25 15:51 kuzelon2 [Lecture 6 - Reinforcement Learning 6]
2024/03/18 15:00 kuzelon2 [Lecture 5 - Reinforcement Learning 5]
2024/03/18 14:57 kuzelon2 [Lecture 4 - Reinforcement Learning 4]
2024/03/18 14:57 kuzelon2 [Lecture 4 - Reinforcement Learning 4]
2024/03/18 14:54 kuzelon2 [Lecture 3 - Reinforcement Learning 3]
2024/03/11 15:59 kuzelon2 [Lecture 4 - Reinforcement Learning 4]
2024/03/04 14:47 kuzelon2 [Lecture 3 - Reinforcement Learning 3]
2024/02/26 15:02 kuzelon2 [Lecture 1 - Reinforcement Learning 1]
2024/02/26 15:01 kuzelon2 [Lecture 1 - Reinforcement Learning 1]
2024/02/26 14:49 kuzelon2 [Lecture 1 - Reinforcement Learning 1]
2024/02/26 14:45 kuzelon2 [Lecture 2 - Reinforcement Learning 2]
2024/02/16 15:13 souregus
2024/02/16 15:12 souregus [Lecture 7 - Natural Language Processing 1]
2024/02/16 14:07 kuzelon2
2024/02/09 10:14 external edit
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courses:smu:lectures [2024/04/08 10:29]
souregus
[Lecture 7 - Natural Language Processing 1]
courses:smu:lectures [2024/05/29 15:07]
(current)
kuzelon2
[Lecture 3 - Reinforcement Learning 3]
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RL & NLP are available online.
RL & NLP are available online.
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You are strongly discouraged from using this course's materials from previous years as you would run into confusions.
The RL part of the course is heavily based on the RL course of prof Emma Brunskill. The relevant lectures from prof Brunskill's course are: [[https://youtu.be/FgzM3zpZ55o|Lecture 1]],[[https://youtu.be/E3f2Camj0Is|Lecture 2]], [[https://youtu.be/dRIhrn8cc9w|Lecture 3]], [[https://youtu.be/j080VBVGkfQ|Lecture 4]], [[https://youtu.be/buptHUzDKcE|Lecture 5]], [[https://youtu.be/gOV8-bC1_KU|Lecture 6]], [[https://youtu.be/RN8qpSs8ozY|Lecture 11]].
The RL part of the course is heavily based on the RL course of prof Emma Brunskill. The relevant lectures from prof Brunskill's course are: [[https://youtu.be/FgzM3zpZ55o|Lecture 1]],[[https://youtu.be/E3f2Camj0Is|Lecture 2]], [[https://youtu.be/dRIhrn8cc9w|Lecture 3]], [[https://youtu.be/j080VBVGkfQ|Lecture 4]], [[https://youtu.be/buptHUzDKcE|Lecture 5]], [[https://youtu.be/gOV8-bC1_KU|Lecture 6]], [[https://youtu.be/RN8qpSs8ozY|Lecture 11]].
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**Note:** //This lecture is heavily based on a lecture by Prof Emma Brunskill (all potential errors are likely mine). There was a typo in the pseudocode of SARSA - the action sampled inside the loop should be sampled from \pi(s_{t+1}) instead of \pi(s_t). The error remains in the video. //
**Note:** //This lecture is heavily based on a lecture by Prof Emma Brunskill (all potential errors are likely mine). There was a typo in the pseudocode of SARSA - the action sampled inside the loop should be sampled from \pi(s_{t+1}) instead of \pi(s_t). The error remains in the video. //
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**Erratum:** There is an error on slide 73, where we should be updating Q(b,right) - we are always updating the state with the "small" ladybug symbol, Thanks to M. Komínek for discovering this error.
**Relevant videos from Prof Brunskill's course:** [[https://youtu.be/j080VBVGkfQ|Lecture 4]]
**Relevant videos from Prof Brunskill's course:** [[https://youtu.be/j080VBVGkfQ|Lecture 4]]
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==== Lecture 8 - Natural Language Processing 2 ====
==== Lecture 8 - Natural Language Processing 2 ====
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** Vector models: ** [[https://drive.google.com/file/d/1EiAeLQLxy2F_fE-ZPxuIMVFi-CUUl0AA/view?usp=share_link| slides]]
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**Video:** [[https://drive.google.com/file/d/1EhQ0bVdZlbhHkUFRZ1Gcd8U_woDmelDN/view?usp=share_link |google-drive]]
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==== Lecture 9 - Natural Language Processing 3 ====
==== Lecture 9 - Natural Language Processing 3 ====
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** Matrix models: ** [[https://drive.google.com/file/d/1GuHzTu5XWBj9vqvfdkfCIL2AeFg6ao-L/view?usp=share_link | slides]]
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**Video:** [[https://drive.google.com/file/d/1EoEjaxDXBwLj_Lctiwel9fS402v0JD8K/view?usp=sharing | google-drive]]
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==== Lecture 10 - Natural Language Processing 4 ====
==== Lecture 10 - Natural Language Processing 4 ====
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** Neural models: ** [[https://drive.google.com/file/d/1HufWicAqTYJvJLel8mEGbEEEdSoak-Dr/view?usp=share_link | slides]]
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**Video:** [[https://drive.google.com/file/d/1HvOZf9kvidmgGtmQcAHDUnp_R9MCdWyb/view?usp=share_link | google-drive]]
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==== Lecture 11 - Computational Learning Theory 1 ====
==== Lecture 11 - Computational Learning Theory 1 ====
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{{ :courses:smu:colt-1.pdf |COLT - lecture 1}}
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**Slides:**
{{ :courses:smu:colt-1.pdf | COLT - lecture 1}}
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**Video:** [[https://www.youtube.com/watch?v=e6XCe84AYEc&list=PLQL6z4JeTTQlgt77fhOe2Jovjjz4THF_G&index=2 | COLT - lecture 1]]
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==== Lecture 12 - Computational Learning Theory 2 ====
==== Lecture 12 - Computational Learning Theory 2 ====
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{{ :courses:smu:colt-2.pdf |COLT - lecture 2}}
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**Slides:**
{{ :courses:smu:colt-2.pdf |COLT - lecture 2}}
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**Video:** [[https://www.youtube.com/watch?v=1oK1zcl7lpA&list=PLQL6z4JeTTQlgt77fhOe2Jovjjz4THF_G&index=3 | COLT - lecture 2]]
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==== Lecture 13 - Computational Learning Theory 3 ====
==== Lecture 13 - Computational Learning Theory 3 ====
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{{ :courses:smu:colt-3.pdf |COLT - lecture 3}}
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**Slides:**
{{ :courses:smu:colt-3.pdf |COLT - lecture 3}}
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**Video:** [[https://www.youtube.com/watch?v=6DIJdKXoggY&list=PLQL6z4JeTTQlgt77fhOe2Jovjjz4THF_G&index=4 | COLT
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lecture 3]]
courses/smu/lectures.1712564940.txt.gz
· Last modified: 2024/04/08 10:29 by
souregus