Lecture 02019/02/19Course Logistics [slides]

Registration: [Google Form]

Lecture 12019/02/26Introduction [slides] (video)

Guest Lecture (R103)[PyTorch Tutorial]

Lecture 22019/03/05Neural Network Basics [slides] (video)

Suggested Readings:

[Linear Algebra]

[Linear Algebra Slides]

[Linear Algebra Quick Review]

A12019/03/05A1: Dialogue Response Selection[A1 pages]

Lecture 32019/03/12Backpropagation [slides] (video)

Word Representation [slides] (video)

Suggested Readings:

[Learning Representations]

[Vector Space Models of Semantics]

[RNNLM: Recurrent Neural Nnetwork Language Model]

[Extensions of RNNLM]

[Optimzation]

Lecture 42019/03/19Recurrent Neural Network [slides] (video)

Basic Attention [slides] (video)

Suggested Readings:

[RNN for Language Understanding]

[RNN for Joint Language Understanding]

[Sequence-to-Sequence Learning]

[Neural Conversational Model]

[Neural Machine Translation with Attention]

[Summarization with Attention]

[Normalization]

A22019/03/19A2: Contextual Embeddings[A2 pages]

Lecture 52019/03/26Word Embeddings [slides] (video)

Contextual Embeddings - ELMo [slides] (video)

Suggested Readings:

[Estimation of Word Representations in Vector Space]

[GloVe: Global Vectors for Word Representation]

[Sequence Tagging with BiLM]

[Learned in Translation: Contextualized Word Vectors]

[ELMo: Embeddings from Language Models]

[More Embeddings]

2019/04/02Spring BreakA1 Due

Lecture 62019/04/09Transformer [slides] (video)

Contextual Embeddings - BERT [slides] (video)

Gating Mechanism [slides] (video)

Suggested readings:

[Contextual Word Representations Introduction]

[Attention is all you need]

[BERT: Pre-training of Bidirectional Transformers]

[GPT: Improving Understanding by Unsupervised Learning]

[Long Short-Term Memory]

[Gated Recurrent Unit]

[More Transformer]

Lecture 72019/04/16Reinforcement Learning Intro [slides] (video)

Basic Q-Learning [slides] (video)

Suggested Readings:

[Reinforcement Learning Intro]

[Stephane Ross' thesis]

[Playing Atari with Deep Reinforcement Learning]

[Deep Reinforcement Learning with Double Q-learning]

[Dueling Network Architectures for Deep Reinforcement Learning]

A32019/04/16A3: RL for Game Playing[A3 pages]

Lecture 82019/04/23Policy Gradient [slides] (video)

Actor-Critic (video)

More about RL [slides] (video)Suggested Readings:

[Asynchronous Methods for Deep Reinforcement Learning]

[Deterministic Policy Gradient Algorithms]

[Continuous Control with Deep Reinforcement Learning]

A2 Due

Lecture 92019/04/30Generative Adversarial Networks [slides] (video)

(Lectured by Prof. Hung-Yi Lee)

Lecture 102019/05/07Convolutional Neural Networks [slides]

A42019/05/07A4: Drawing[A4 pages]

2019/05/14BreakA3 Due

Lecture 112019/05/21Unsupervised Learning [slides]

NLP Examples [slides]

Project Plan [slides]

Special2019/05/28 Company WorkshopRegistration: [Google Form]

2019/06/04BreakA4 Due

Lecture 122019/06/11Project Progress Presentation

Course and Career Discussion

Special2019/06/18Company WorkshopRegistration: [Google Form]

Lecture 132019/06/25Final Presentation