Classes begin January 14. See CMU Academic Calendar.
All homework is due 10 minutes before lecture start.
Date Topic
Reading
Part I: Background
Tuesday
January
14
Thursday
January
16
Classification, Logistic Regression
Tuesday
January
21
Gradient Descent, Stochastic Gradient Descent
Thursday
January
23
Homework 1 out (pdf, zip)
Deep Learning Software
Tuesday
January
28
Back Propagation
Thursday
January
30
Tuesday
February
4
Thursday
February
6
Homework 1 due
Background: Convolutional Neural Networks I
Tuesday
February
11
Background: Second Order Optimization
Part II: Explanations
Thursday
February
13
Homework 2 out (pdf, zip)
Paper Discussion: Representer Point Selection for DNN
Tuesday
February
18
Thursday
February
20
Paper Discussion: Axiomatic Attribution for Deep Networks
Tuesday
February
25
Paper Discussion: Influence-Directed Explanations for CNNsGuest speaker: Klas Leino
Thursday
February
27
Tuesday
March
3
Homework 2 due
Paper Discussion: Shapley Values and Cooperative Game TheoryGuest speaker: Ankur Taly
Thursday
March
5
Homework 3 Part 1 out (zip+pdf)
Paper Discussion: Concept-based ExplanationsGuest speaker: Amirata Ghorbani
Tuesday
March
10
No Class: Spring Break
Thursday
March
12
No Class: Spring Break
Part III: Adversarial Learning
Tuesday
March
17
Homework 3 Part 2 out (see canvas)
Teleconferencing Debugging Session and Office Hours
Thursday
March
19
Paper Discussion: Adversarial LearningGuest speaker: Nicolas Papernot
Tuesday
March
24
Paper Discussion: Real-world Adversarial AttacksGuest speaker: Mahmood Sharif
Thursday
March
26
Paper Discussion: Robustness and Adversarial LearningGuest speaker: Nicholas Carlini
Tuesday
March
31
Homework 3 due
(approximate date) Homework 4 out
Paper Discussion: Generative Adversarial Nets
Part IV: Privacy and Fairness
Thursday
April
2
Tuesday
April
7
(approximate date) Homework 4 due
(approximate date) Homework 5 out
Paper Discussion: Fairness in Deep Learning
Thursday
April
9
Background: Recurrent Neural Networks I
Tuesday
April
14
Thursday
April
16
No Class: CMU Carnival (might become lecture)
Tuesday
April
21
Paper Discussion: Bias In Word EmbeddingsGuest speaker: Kai-Wei Chang
Thursday
April
23
TBD
Tuesday
April
28
(approximate date) Homework 5 due
Paper Discussion: Bias in NLP tasksGuest speaker: Caleb Lu
Thursday
April
30
TBD

* All schedules are subject to change over the course.