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ML Systems challenges; Multilingual Coref; Unsupervised NMT; Human MT performance; Neural Lattice Language Models; Norms comparison; Are GANs created equal

Enjoy your morning coffee ☕️ with the thought-provoking posts in this issue of NLP News: Listen to Mi
NLP News
ML Systems challenges; Multilingual Coref; Unsupervised NMT; Human MT performance; Neural Lattice Language Models; Norms comparison; Are GANs created equal
By Sebastian Ruder • Issue #19 • View online
Enjoy your morning coffee ☕️ with the thought-provoking posts in this issue of NLP News: Listen to Michael Jordan outline challenges for applying ML to systems; train your own coreference resolution model in any language; train an Unsupervised Neural Machine Translation model; discover how Microsoft matched human performance on Machine Translation; learn about Neural Lattice Language Models; and many more.
This edition also features a new category, Best Visualization. Do you find this helpful 💡or boring 💤? Let me know!

Presentations and slides
SysML 18: Michael Jordan, Perspectives and Challenges
SysML 18: Michael Jordan, Perspectives and Challenges
Tools and implementations
Best visualization
The relationship between different normalizations in neural networks
The relationship between different normalizations in neural networks
Blog posts and other articles
CRF Layer on the Top of BiLSTM
Kipoi: Model zoo for genomics
Learning to Represent Words by how They’re Spelled
What is wrong with VAEs?
Industry insights
An Introduction to Snips NLU, the Open Source Library behind Snips Embedded Voice Platform
Allen Institute CEO says A.I. graduates should take oath
Muse, an AI-powered parenting bot, wants to help parents help their children succeed
Paper picks
Did you enjoy this issue?
Sebastian Ruder

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