CS485/685 - Schedule


This is a tentative schedule only.  As the course progresses, the schedule will be adjusted.

[GBC] Ian Goodfellow, Yoshua Bengio and Aaron Courville, Deep Learning (in progress) freely available online
[HTF]
Trevor Hastie, Robert Tibshirani and Jerome Friedman, Elements of Statistical Learning (2nd edition, 2009) freely available online
[D] Hal Daume III, A Course in Machine Learning (in progress) freely available online
[B] Christopher Bishop, Pattern Recognition and Machine Learning (2006)
[RN] Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach (3rd Edition) (2010)
[M] Kevin Murphy, Machine Learning: A Probabilistic Perspective (2012)
[MRT] Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar, Foundations of Machine Learning (2012)
[SSBD] Shai Shalev-Shwartz, Shai Ben-David, Understanding Machine Learning: From Theory to Algorithms (2014)

New: Notation reference sheet for the slides below

Lecture
Date
Topic
Readings (textbooks)
1
Jan 5
Introduction to Machine Learning (slides)

2
Jan 7
Decision trees (slides (slide 20 corrected Feb 10))
[RN] Sec. 18.1-18.4, [HTF] Sec. 9.2, [D] Chapt. 1, [B] Sec. 14.4, [M] Sec. 16.2
3
Jan 12
K-nearest neighbours (slides (slide 6 corrected Jan 27))
[RN] Sec. 18.8.1, [HTF] Sec. 2.3.2, [D] Chapt. 2, [B] Sec. 2.5.2, [M] Sec. 1.4.2
4
Jan 14
Linear regression (slides)
[RN] Sec. 18.6.1, [HTF] Sec. 2.3.1, [D] Sec. 6.6, [B] Sec. 3.1, [M] Sec. 1.4.5
5
Jan 19
Statistical learning (slides) [RN] Sec. 20.1, 20.2, [M] Sec. 2.2, 3.2
6
Jan 21 Linear regression by maximum likelihood, maximum a posteriori, Bayesian learning (slides) [B] Sec. 3.1-3.3, [M] Chap. 7

Jan 25
Assignment 1 due (11:59 pm)

7
Jan 26
Mixture of Gaussians (slides (slide 5 corrected Feb 1))
[B] Sec. 4.2, [M] Sec. 4.2
8
Jan 28
Logistic regression, generalized linear models (slides)
[RN] Sec. 18.6.4, [B] Sec. 4.3, [M] Chap. 8, [HTF] Sec. 4.4
9
Feb 2
Perceptrons, single layer neural networks (slides)
[D] Chapt. 3, [HTF] Chapt. 11, [B] Sec. 4.1.7, 5.1, [M] Sec. 8.5.4, [RN] Sec. 18.7
10
Feb 4
Multi-layer Neural networks, Backpropagation (slides (slide 6 corrected Feb 7, slide 14 corrected Feb 10))(Quick Recap)
[D] Chapt. 8, [HTF] Chapt. 11, [B] Sec. 5.2, 5.3, [M] Sec. 16.5, [RN] Sec. 18.7

Feb 8
Assignment 2 due (11:59 pm)

11
Feb 9
Guest lecture by Theophanis Stratopoulos
Two papers:
1) Emerging Technology Adoption and Expected Duration of Competitive Advantage
2) Financial Reports Based Proxies for Bargaining Power of Buyers and Sellers
12
Feb 11
Midterm (in class)


Feb 16
Reading break (no class)


Feb 18
Reading break (no class)

13
Feb 23
Kernel methods (slides (slides 7,8 corrected Feb 26))

[B] Sec. 6.1, 6.2 [M] Sec. 14.1, 14.2 [H] Chap. 9 [HTF] Chap. 6
14
Feb 25
Gaussian Processes (slides (slide 11 corrected March 2))
[B] Sec. 6.4 [M] Chap. 15 [HTF] Sec. 8.3

Feb 29
Project proposal due (11:59 pm)

15
Mar 1
Support vector machines (slides (slide 13 corrected March 8))
[B] Sec. 7.1 [D] Sec. 6.7 [HTF] Chap. 12 [M] Sec. 14.5 [RN] Sec. 18.9 [MRT] Chap. 4
16
Mar 3
Support vector machines continued (slides)
[B] Sec. 7.1 [D] Sec. 6.7 [HTF] Chap. 12 [M] Sec. 14.5 [RN] Sec. 18.9 [MRT] Chap. 4

Mar 7
Assignment 3 due (11:59 pm)

17
Mar 8
Hidden Markov models (slides (slides 12-18 corrected March 23)) [RN] Sec. 15.3 [B] Sec. 13.1-13.2 [M] Sec. 17.3-17.5
18
Mar 10
Hidden Markov models continued (slides (slides 8-16 corrected March 23)) [RN] Sec. 15.3 [B] Sec. 13.1-13.2 [M] Sec. 17.3-17.5
19
Mar 15
Deep neural networks (slides) [GBC] Chap. 6-9
20
Mar 17
Convolutional neural networks (slides)
[GBC] Chap. 10

Mar 23
Assignment 4 due (11:59 pm)

21
Mar 22
Recurrent and recursive neural networks (slides)
[GBC] Chap. 11
22
Mar 24
Ensemble learning: bagging and boosting (slides)
[RN] Sec 18.10, [M] Sec. 16.2.5, [B] Chap. 14, [HTF] Chap. 15-16, [D] Chap. 11
23
Mar 29
Bagging, decision forests and distributed computing (slides)
[RN] Sec 18.10, [M] Sec. 16.2.5, [B] Chap. 14, [HTF] Chap. 15-16, [D] Chap. 11
24
Mar 31
Stream learning (slides)
course wrap up
[M] Sec. 8.5

Apr 6
Assignment 5 due (11:59 pm)


Apr 18
Project report due (11:59 pm)