EMNLP 2020 recap, Minimum viable datasets, Efficiency, Roguelikes for RL Research
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Hi all,I sincerely hope that this year was an extreme outlier and that 2021 will be again more in-distribution. I hope you have time to relax and spend time with your loved ones. On a personal note, growing up I never understood why May you live in interesting times (Interesting Times is the title of a book by a favourite author of mine) may be considered a curse. I think I have a better sense of it now.While personal interactions have been limited mostly to the online setting this year, I am grateful for everyone I've had the chance to interact with or meet this year. Thank you for brightening my 2020. I hope I get to meet some of you in person again next year.This newsletter includes a (very) brief recap of my EMNLP 2020 and a discussion of datasets that are minimally viable to evaluate the capabilities of a model. I highlight some interesting research areas related to efficiency and—on a more fun note—recent research in reinforcement learning that leverages roguelikes and procedural generation. I also cover miscellaneous blog posts and articles, among them a 385-page (!) ML compendium.I really appreciate your feedback, so let me know what you love ❤️ and hate 💔 about this edition. Simply hit reply on the issue.If you were referred by a friend, click here to subscribe. If you enjoyed this issue, give it a tweet 🐦.
EMNLP 2020 recap, Minimum viable datasets, Efficiency, Roguelikes for RL Research
EMNLP 2020 recap, Minimum viable datasets…
EMNLP 2020 recap, Minimum viable datasets, Efficiency, Roguelikes for RL Research
Hi all,I sincerely hope that this year was an extreme outlier and that 2021 will be again more in-distribution. I hope you have time to relax and spend time with your loved ones. On a personal note, growing up I never understood why May you live in interesting times (Interesting Times is the title of a book by a favourite author of mine) may be considered a curse. I think I have a better sense of it now.While personal interactions have been limited mostly to the online setting this year, I am grateful for everyone I've had the chance to interact with or meet this year. Thank you for brightening my 2020. I hope I get to meet some of you in person again next year.This newsletter includes a (very) brief recap of my EMNLP 2020 and a discussion of datasets that are minimally viable to evaluate the capabilities of a model. I highlight some interesting research areas related to efficiency and—on a more fun note—recent research in reinforcement learning that leverages roguelikes and procedural generation. I also cover miscellaneous blog posts and articles, among them a 385-page (!) ML compendium.I really appreciate your feedback, so let me know what you love ❤️ and hate 💔 about this edition. Simply hit reply on the issue.If you were referred by a friend, click here to subscribe. If you enjoyed this issue, give it a tweet 🐦.