The Thesis Review

[08] He He - Sequential Decisions and Predictions in NLP

Sep 25, 2020
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1
Introduction
00:00 • 2min
2
How I Decided to Do a PhD
01:59 • 3min
3
Sequential Decisions and Predictions in NLP
04:40 • 2min
4
How Machine Learning Interacts With Structure Prediction
06:13 • 3min
5
How to Combine Imitation Learning and Reinforcement Learning
09:32 • 5min
6
Offline Reinforcement Learning for Text Generation
14:24 • 2min
7
How to Frame NLP Problems as Sequential Decision Making
16:27 • 6min
8
How to Adapt a Pre-Trained Language Model to a Conditional Task
22:09 • 2min
9
How to Optimize a Language Model for Funniness
24:26 • 2min
10
How to Use Reinforcement Learning to Solve Complex Problems
26:22 • 2min
11
Coaching: A Way to Improve Text Generation
28:47 • 4min
12
The Relationship Between the Oracle and the Trust Region
32:25 • 5min
13
The Variation of Key Learning
37:18 • 2min
14
How to Model the Knowledge Graph of Two Different Agents
38:59 • 2min
15
The Benefits of Modeling the Information of Friends
41:00 • 3min
16
The Future of Translation Models
43:45 • 4min
17
The PhD and the PhD in Text Generation
47:38 • 2min
18
The Importance of a Test-Time Distribution
49:41 • 4min
19
Scaling Up Models to Improve Robustness
53:34 • 3min
20
How to Handle Failure in the First Year of a PhD
56:29 • 4min