This is the 2017 syllabus. The 2018 syllabus will be substantially different in places, but you’re welcome to refer to previous material here.

Week Day Plan
Week Day Plan
Week 1 Jan 16 Lecture Introduction

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Jan 19 Lecture Probability, language models, and conditional language models

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Week 2 No in-person lectures in week 2

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Jan 24 Lab Latent-variable translation models

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Week 3 Jan 30 Lecture Phrase-based translation and decoding

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Feb 02 Lecture Evaluation of translation systems

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Week 4 Feb 06 Lecture Words and Morphology

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Feb 09 Coursework Coursework 1 due at 4pm
Lecture Morphology (continued); maximum entropy models

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Week 5 Feb 13 Lecture Neural probabilistic language models

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Feb 14 Lab Neural probabilistic language models

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Feb 16 Lecture Conditional neural language models

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No class the week of Feb 20
Week 6 Feb 27 Lecture Large vocabulary language modeling

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Mar 02 Lecture Large vocabulary translation modeling

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Week 7 Mar 06 Lecture Attention

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Mar 07 Lab Coursework 2 support
Mar 09 Lecture Using monolingual data in NMT

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Week 8 Mar 13 Coursework Coursework 2 due at 4pm
Lecture Multi-source and zero-shot translation

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Mar 16 Lecture Syntax and translation

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Week 9 Mar 20 Lecture Recurrent neural network grammars

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Mar 23 Lecture Minimum risk training and evaluation revisited

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Week 10 Mar 27 Lecture Decipherment

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Mar 28 Lab Coursework 3 support
Mar 30 Lecture History (final lecture)

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Week 11 No lectures or labs. Work on final coursework.
Week 12 Apr 13 Coursework Coursework 3 due at 4pm

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