CS470/570 Artificial Intelligence — Schedule, Fall 2016

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CS470/570 Schedule

# Date Topic To do
For today For future Due date
1 Wednesday, Aug 31 Overview of CS470/570
This term the focus will be on computational linguistics, and in particular computational semantics.
FPS, chs. 1 and 2 9-02
The Scala Programming Language
2 Friday, Sep 2 Introduction to Scala
FPS, chs. 1 and 2 See Scala download info on course web page 9-07
FPS, sec. 3.1–3.4 9-12
Lecture notes for lecs. 2&4 9-17
Monday, Sep 5 Labor Day: No class
See Scala download info on course web page 9-07
FPS, sec. 3.1–3.4 9-12
Lecture notes for lecs. 2&4 9-17
3 Wednesday, Sep 7 Downloading and running Scala
See Scala download info on course web page FPS, sec. 3.1–3.4 9-12
Lecture notes for lecs. 2&4 9-17
4 Friday, Sep 9 Search in AI (Code examples: General-purpose blind-search algorithm: SearchAlg.scala. Map-coloring application: MapColor.scala
Slides (Prof. Scassellati) FPS, sec. 3.1–3.4 9-12
Terminological and algorithmic notes on search Lecture notes for lecs. 2&4 9-17
Saturday, Sep 10
Problem Set 1 9-17
Lecture notes for lecs. 2&4 9-17
5 Monday, Sep 12 Case classes. Lists and recursion
FPS, sec. 3.1–3.4 FPS, all of ch. 3 9-14
Problem Set 1 9-17
Lecture notes for lecs. 2&4 9-17
Lecture notes for lecs. 5–6 9-23
6 Wednesday, Sep 14 Recursive functions on recursive data structures
FPS, ch. 3
Problem Set 1 9-17
Lecture notes for lecs. 2–4 9-17
Lecture notes for lecs. 5–6 9-23
7 Friday, Sep 16 Functional-programming techniques: map, filter.
Problem Set 1 9-17
Lecture notes for lecs. 5–6 9-23
Problem Set 2 (Available today) 9-23
FPS, ch. 5 9-19
Saturday, Sep 17
Problem Set 1 Problem Set 2 (Available today) 9-23
8 Monday, Sep 19 More on functional programming: flatMap, zip.
FPS, ch. 5 SLP sec. 18.0, 18.1, 12.0–12.3 9-21
Problem Set 2 9-23
Lecture notes for lecs. 5–6 9-23
Lecture notes for lec. 7
Lecture notes for lec. 8 (class solution to puzzle) 9-21
9 Wednesday, Sep 21 Yet More on functional programming: Laziness vs. strictness. Streams. Lecture notes in long comment in StreamDemo.scala. You also need Logger.scala
FPS, ch. 5 SLP sec. 18.0, 18.1, 12.0–12.3 9-21
Problem Set 2 9-23
Lecture notes for lecs. 5–6 9-23
Lecture notes for lec. 7
Lecture notes for lec. 8 (class solution to puzzle) 9-21
Grammar and the Syntax-Semantics Interface
10 Friday, Sep 23 Grammars for natural and artificial languages
Problem Set 2 SLP 17.0, 17.1, 17.3 9-26
SLP, secs 12.0--12.3 SLP secs. 17.0, 17.1, 17.3 9-26
Problem Set 2 9-23
Lecture notes for lecs. 5–6 9-23
Lecture notes for lec. 7 9-23
11 Monday, Sep 26 X-bar theory.
Notes on X-bar theoryXbar citation.) from BU linguistics course
12 Wednesday, Sep 28 Internal representation: predicate calculus. Events.
SLP 17.1, 17.3.1–17.3.3
13 Friday, Sep 30 Three meanings of "meaning"
Lecture notes 9-30
SLP, sec. 17.3.3 9-30
Notes on λ-calculus for lec. 12
14 Monday, Oct 3 More depth on the syntax-semantics interface. Principle of compositionality and its difficulties.
SLP, sec. 18.0–18.2 [[ ?? ]]
15 Wednesday, Oct 5 Suppose we let the meaning of an S of the form NP VP be the meaning of VP applied to the meaning of NP. So the meaning of "Sally skis" is M(skis)(M(Sally)) = ski(sally13), assuming proper names such as "Sally" are resolved into internal nodes in your mental model for particular people you know, here parodied as symbols ending in funny numbers. But then what do we do with "Every Swiss skis"? What is M(Every Swiss)?
SLP sec. 13.2, 18,0–18.3, 18.3, 19.0–19.3
16 Friday, Oct 7 The λ-calculus
Lecture notes
17 Monday, Oct 10 Advantages of immutable data structures.
SLP, sec. 17.4
18 Wednesday, Oct 12 The Scala compiler can be our λ-expression type checker. Lec18.scala
19 Friday, Oct 14 Further ramifications: Filling out abstract type T as Boolean in Lec18.scala: Lec18Boolean.scala. We could also let symbols ending in "I" produce S-expressions: Lec18Sexp.scala
13.0–13.3
20 Monday, Oct 17 Midterm
Midterm
21 Monday, Oct 24 Top-down and bottom-up parsing. The combinatorics of parsing: The complexity grows exponentially the length of the sentences grows, because the number of answers grows exponentially, due to the ambiguity problem.
22 Wednesday, Oct 26 Dynamic programming (Simplest application of dynamic programming: memoization)
SLP, sec. 3.11
23 Friday, Oct 28 Chart parsing: Earley algorithm.
SLP, sec. 13.4 SLP, sec. 18.3 10-31
Lecture notes SLP, 15.0–15.3 11-02
24 Monday, Oct 31 More on chart parsing
SLP, sec. 18.3 10-31
Unification grammar paper by Stuart Shieber (pp. 1--30) 11-02
SLP, 15.0–15.3 11-02
25 Wednesday, Nov 2 Scope ambiguities: Quantifiers, negation, modalities
SLP, sec. 18.3 SLP, 15.0–15.3 11-02
Unification grammar paper by Stuart Shieber (pp. 1--30) 11-02
s
Parsing and Unification
26 Friday, Nov 4 Feature grammars: introduction    
SLP, 15.0–15.3
Lecture notes
Supplemental lecture notes
Unification grammar paper by Stuart Shieber (pp. 1--30) [[ ?? ]]
27 Monday, Nov 7 Feature grammars and agreement; bidirectional propagation. Long-distance dependencies.
Lecture notes
28 Wednesday, Nov 9 Subsumption and unification
Briscoe and Carroll paper on robust LR parsing with unification grammars 11-11
Lecture notes
29 Friday, Nov 11 Unification parsing
Briscoe and Carroll paper on robust LR parsing with unification grammars 11-11
30 Monday, Nov 14 Integrating unification and Earley's algorithm
Briscoe and Carroll paper on robust LR parsing with unification grammars
Shieber paper on including unification in Early parser Problem Set y 11-18
31 Wednesday, Nov 16 Wrap up unification parsing
Notes on probabiilty Problem Set y 11-18
SLP, sec. 14.3 11-18
Probabilistic Techniques
32 Friday, Nov 18 Statistical parsing: PCFGs
SLP: 14.0–14.2 Problem Set y 11-18
SLP, sec. 14.3 11-18
SLP, sec. 14.4--14.6.1 11-28
33 Monday, Nov 28 Machine learning: statistical learning theory.
SLP, sec. 14.3
Problem Set y SLP, sec. 14.4--14.6.1 11-28
34 Wednesday, Nov 30 Improving PCFGs (lexicalization)
SLP, sec. 14.4--14.6.1 SLP, sec. 25.4--25.9 12-02
35 Friday, Dec 2 Machine translation: Bypassing classical semantics
SLP, sec. 25.0--25.3 SLP, sec. 25.4--25.9 12-02
36 Monday, Dec 5 Learning to translate (and do other NL tasks)
SLP, sec. 25.4--25.9
Problem Set z 12-09
37 Wednesday, Dec 7 TBA
Problem Set z 12-09
38 Friday, Dec 9 Course summation
Problem Set z
-- Monday, Dec 19, 2:00 PM Final exam

NOTE: The final exam CS470/570 is scheduled for Dec. 19. Please do not make any travel plans that conflict with this date.

CS570 Schedule

1 Tuesday, Sep 6, 4:00 PM CS570 organizational meeting

Note Xbar citation
The X-bar notes are from "Syntax I," course LX522, Fall 2001. They are by Prof. Paul Hagstrom. They show what kind of evidence impresses linguists. The actual statement of X-bar theory starts on p. 4 (slide 19). [Back]