Classes start on January 16, 2018
| Date | Topic | Reading | Notes |
|---|---|---|---|
| Tue, Jan 16 | Course Overview |
CMU Computing Policy CMU Policy on Academic Integrity Nature Review on Deep Learning Classification Intro |
Course overview Note |
| PART I: Machine Learning Basics | |||
| Thur, Jan 18 | Intro to Machine Learning I (Linear Algebra Review, Logistic Regression) |
Deep Learning Book, CH2 Linear Classification Basics |
Notes |
| Tue, Jan 23 | Intro to Machine Learning II (Gradient Descent, Stochastic Gradient Descent)) | Stochastic Gradient Descent Deep Learning Book, CH3 | Notes |
| Thur, Jan 25 | Intro to Machine Learning III (Stochastic Gradient Descent)) HW1Out | Stochastic Gradient Descent Deep Learning Book, CH4 + CH8:8.1.3 | Notes |
| PART II: Intro to Deep Learning | |||
| Tue, Jan 30 | Deep Learning Software (In preparation for HW 1) | Documentation of Keras Documentation of Theano | Notes |
| Thur, Feb 1 | Back Propagation |
Back Propagation |
Notes |
| Tue, Feb 6 | Deep Feedforward Networks |
Deep Learning Book, CH6 Setting up the Data and Model |
Notes |
| Thur, Feb 8 | DFN Training |
Deep Learning Book, CH6 Learning and Evaluation |
Notes |
| Tue, Feb 13 | Convolutional Neural Networks I | CNN Architecture Deep Learning Book, CH9 | Notes |
| Thur, Feb 15 | Convolutional Neural Networks II HW1 In |
CNN Visualization Deep Learning Book, CH9 | Notes |
| PART III: Explanation for Deep Neural Networks | |||
| Tue, Feb 20 | Paper Discussion: Axiomatic Attribution for Deep Networks Guest Lecture Ankur Taly (Google) | Axiomatic Attribution for Deep Networks | Notes |
| Thur, Feb 22 | Deep Learning Software
(In preparation for HW 2)
HW2 Out : code files |
Documentation of Keras Documentation of Tensorflow | Notes |
| Tue, Feb 27 | Paper Discussion: Influence-Directed Explanations for CNN | Influence-Directed Explanations for CNN | Notes |
| Thur, Mar 1 | Paper Discussion: Influence functions Guest Lecture: Pang Wei Koh (Stanford) | Understanding Black-box Predictions via Influence Functions | Notes |
| Tue, Mar 6 | Paper Discussion: Influence-Directed Explanations for CNN (Continued) | Influence-Directed Explanations for CNN | Notes |
| PART IV: Adversarial Learning | |||
| Thur, Mar 8 | Paper Discussion: Adversarial Settings in Deep Learning Guest Lecture: Matt Fredrikson(CMU) | The Limitations of DL in Adversarial Settings | notes |
| Tue, Mar 13 | No Class: Spring Break | ||
| Thur, Mar 15 | No Class: Spring Break | ||
| Tue, Mar 20 | Paper Discussion: Defensive Distillation Guest Lecture: Nicholas Carlini (UC Berkeley) HW2 In | Towards Evaluating the Robustness of Neural Networks | Notes |
| Thur, Mar 22 | Paper Discussion: Detecting Adversarial Samples Guest Lecture: Saurabh Shintre (Symantec) | Detecting Adversarial Samples from Artifacts | Notes |
| Tue, Mar 27 | HW3 code files environment HW3 Preparation Generative Models |
Notes | |
| Thur, Mar 29 | Paper Discussion: Generative Adversarial Networks | Generative Adversarial Nets | Notes |
| PART V: Recurrent Neural Networks | |||
| Tue, Apr 3 | Vector Representations | Word2vec | Notes |
| Thur, Apr 5 | Recurrent Neural Network I | Deep Learning Book, CH10 | Notes |
| Tue, Apr 10 | Recurrent Neural Network II | Deep Learning Book, CH10 | Notes |
| Thur,Apr 12 | Paper Discussion: Bias In Word Embeddings Guest Lecture: James Zou(Stanford) | Man is to Computer Programmer as Woman is to Homemaker? Human-like Bias in Langauge Models | Notes |
| Tue, Apr 17 | Paper Discussion: Explanation for RNN I
Guest Lecture: David Alvarez Melis HW3 In(Extended for 1 day, See Piazza) |
A causal framework for explaining the predictions of black-box sequence-to-sequence models | Notes |
| Thur, Apr 19 | HW4 Out code files CMU Carnival: No class |
||
| Tue, Apr 24 | Explanation for RNN II: Bias in NLP Tasks | Rationalizing Neural Predictions | Notes |
| Thur, Apr 26 | Recurrent Neural Network III: LSTM | Exploding and Vanishing Gradients Understanding LSTMs |
Notes |
| Tue, May 1 | Recurrent Neural Network IV: Sequence to sequence models | Sequence to sequence Models Neural Machine Translation |
Notes |
| Thur, May 3 | Class Wrapup HW4 Due: May 9 |
TBD | Notes |
* All schedules are subject to change over the course.