Suggest edit — Issues in ML Research

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title: "Issues in ML Research"
visibility: public
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# Issues in ML Research

Category: [[machine-intelligence|Machine Intelligence]]

[Read the original document](https://docs.google.com/document/d/1x_64kgD5urKaVkTUv0fGfIpo0yaQMtxoKmZR6ZJxHzI/edit?usp=drivesdk&sa=D&ust=1596495076476000&usg=AOvVaw2kBqJ7h6RIcFQEDk3Yxp04)

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1. Winner’s Curse? On Pace, Progress and Empirical Rigor
   1. https://openreview.net/pdf?id=rJWF0Fywf
2. Are GANs Created Equal?
   1. https://arxiv.org/abs/1711.10337
3. Ali Rahmani Talk
   1. https://www.youtube.com/watch?v=Qi1Yry33TQE
4. Joelle Pineau Talk (Reproducibility, Reusability, Robustness)
   1. https://www.youtube.com/watch?v=Vh4H0gOwdIg
5. LSTMs: A Search Space Odyssey
   1. https://arxiv.org/pdf/1503.04069.pdf
6. Deep Reinforcement Learning That Matters        
   1. https://arxiv.org/abs/1709.06560
7. Deep Reinforcement Learning Doesn’t Work Yet
   1. https://www.alexirpan.com/2018/02/14/rl-hard.html
8. Troubling Trends in Machine Learning Scholarship
   1. https://arxiv.org/abs/1807.03341
9. Improvements that Don’t Add Up: Ad-hoc Retrieval Results since 1998
   1. http://people.cs.uchicago.edu/~tga/pubs/amwz09_cikm.pdf
10. The Mythos of Model Interpretability
   1. https://arxiv.org/pdf/1606.03490.pdf

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*Source: [Original Google Doc](https://docs.google.com/document/d/1x_64kgD5urKaVkTUv0fGfIpo0yaQMtxoKmZR6ZJxHzI/edit?usp=drivesdk&sa=D&ust=1596495076476000&usg=AOvVaw2kBqJ7h6RIcFQEDk3Yxp04)*