Schedule and Syllabus

Monday 14:20-17:20 (CS Building 102)
Thursday 9:10-12:10 (EE Building No. 2 106)
[pdf]

Event Date Description Course Material
Lecture 0 09/11/17
09/14/17		 Course Logistics
[Mon slides] [Thu slides]		 Registration: [Google Form]
A0 Release 09/14/17 Basics [A0 Page]
A0 Due 09/17/17 Basics
Lecture 1 09/18/17
09/21/17
 Introduction
[slides] (Mon video) (Thur video)
Neural Network Basics
[slides] (Mon video) (Thur video) 		Suggested Readings:
  1. [Linear Algebra]
  2. [Linear Algebra Slides]
  3. [Linear Algebra Quick Review]
Link: [Microsoft Azure Registration]
Lecture 2 09/25/17
09/28/17
 Backpropagation
[slides] (Mon video) (Thur video)
Word Representation
[slides] (Mon video) (Thur video)
Sequence Modeling
[slides] (Mon video)
 Suggested Readings:
  1. [Learning Representations by Backpropogating Errors]
  2. [From Frequency to Meaning: Vector Space Models of Semantics]
Lecture 3 10/02/17
10/05/17
 Recurrent Neural Network
[slides] (Thur video)
Recursive Neural Network
[slides] (Thur video)
 Suggested Readings:
  1. [RNNLM: Recurrent Neural Nnetwork Language Model]
  2. [Extensions of RNNLM]
  3. [RNN for Language Understanding]
  4. [RNN for Joint Language Understanding]
  5. [Sequence-to-Sequence Learning]
  6. [Neural Conversational Model]
  7. [Parsing with Compositional Vector Grammars]
  8. [Subgradient Methods for Structure Prediction]
  9. [Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank]
A1 Release 10/05/17 Sequence Labeling [A1 Page] [A1 Slides]
10/09/17 Break
Special 10/12/17 Company Workshop [Company Visit Event] [Photo]
Lecture 4-1
Guest Lecture		 10/16/17
10/19/17
 Word Embeddings (1)
[slides] (Thur video)
Guest Lecture 		Suggested Readings:
  1. [Distributed Representations of Words and Phrases and their Compositionality]
  2. [Efficient Estimation of Word Representations in Vector Space]
  3. [GloVe: Global Vectors for Word Representation]
Lecture 4-2
Guest Lecture		 10/23/17
 Word Embeddings (2)
[slides] (Mon video)

Guest Lecture
by Pei-Hao Su 		[Report Submission] [Question Form]
Note: the submission is due on 10/28
This guest lecture is only for ADL students
Self-Learning
Lecture 4-2		 10/26/17 Break
Word Embeddings (2)
[slides] (Thur video)
A1 Due 10/28/17 Sequence Labeling
A2 Release 10/28/17 Video Captioning [A2 Page] [A2 Slides]
Lecture 5 10/30/17
11/02/17 		Gated RNN
Sequence Generation
[slides] (Mon video) (Thur video)
 Suggested Readings:
  1. [Image Caption Generation]
  2. [Video Caption Generation]
  3. [Speech Recognition]
  4. [Sequence Level Training]
Project Announcement 10/30/17
11/02/17		 Final Project [Project Page] [Project Slides]
Lecture 6 11/06/17
11/09/17
 Special Networks
[slides] (Mon video) (Thur video) 		Suggested Readings:
  1. [CNN for Seq-to-Seq]
  2. [Spatial Transformer]
  3. [Highway Network]
  4. [Pointer Network]
  5. [Memory Network]
Special 11/13/17 Company Workshop [RSVP Form]
Lecture 7 11/16/17
11/20/17
 Advanced Tips for Deep Learning
[slides] (Thur video) (Mon video) 		Suggested Readings:
  1. [Batch Normalization]
  2. [SELU Activation Function]
  3. [Tuning Hyperparameters]
  4. [Knowledge Distillation]
  5. [Capsule]
A2 Due 11/19/17 Video Captioning
Lecture 11/23/17
11/27/17
 Deep Reinforcement Learning (1)
[slides] (Thur video) (Mon video) 		Suggested Readings:
  1. [Reinforcement Learning: An Introduction]
  2. [Stephane Ross’ thesis (Introduction)]
  3. [Modularizing Unsupervised Sense Embeddings]
A3 Release 11/27/17 Game Playing [A3 Page] [A3 Slides] [A3 Video]
Guest Lecture 11/30/17 Guest Lecture
by Dr. Kai-Wei Chang 		Note: This guest lecture is only for MLDS students
Lecture 12/04/17
12/07/17
 Deep Reinforcement Learning (2)
[slides] (Mon video) (Thur video) 		Suggested Readings:
  1. [Playing Atari with Deep Reinforcement Learning]
  2. [Deep Reinforcement Learning with Double Q-learning]
  3. [Dueling Network Architectures for Deep Reinforcement Learning]
  4. [Asynchronous Methods for Deep Reinforcement Learning]
  5. [Deterministic Policy Gradient Algorithms]
  6. [Continuous Control with Deep Reinforcement Learning]
Lecture 12/11/17
12/14/17
 Generative Adversarial Network
[slides] (Mon video) (Thur video) 		Suggested Readings:
  1. [Generative Adversarial Network]
  2. [Conditional GAN]
  3. [Cycle GAN]
A4 Release 12/14/17 Comic Generation [A4 Page] [A4 Slides]
A3 Due 12/16/17 Game Playing
Lecture 12/18/17
12/21/17
 Assignment 1 & 2 Sharing
Lecture 12/25/17
12/28/17
 Sequence Generation by GAN
[slides] (Mon video) (Thur video) 		Suggested Readings:
  1. [Seq GAN]
  2. [Unsupervised Machine Translation]
  3. [Style Transfer]
A4 Due 12/31/17 Comic Generation
01/01/18 Break
Lecture 01/04/18
01/08/18
 All Kinds of GANs [slides] (Thur video)
Project Exhibition 01/15/18 Final Project Presentation [Project Page]
Poster Presentation Schedule:
  1. 13:30-15:00
  2. 15:30-17:00
  3. 17:30-19:00
Project Exhibition 01/18/18 HTC AI Project Competition [Project Page]
Project Due 01/20/18 Final Project