CS291K Advanced Data Mining -Schedule

Date	Topic	Comments
Apr 2	Course Introduction
Apr 4	Neural Network	Basic Concepts
Apr 9	Guest Speaker: Andrew Mutz for course project topics
Apr 11	Neural Network Training + CNN
Apr 13	RNN + LSTM	Friday make-up
Apr 16	Word Embedding Distributed Representations of Words and Phrases and their Compositionality - NIPS'13 Deep contextualized word representations - NAACL'18 Optional: GloVe: Global Vectors for Word Representation - EMNLP'14 A Neural Probabilistic Language Model - JMLR'03 Indexing by Latent Semantic Analysis - JASIS'90	Basic Concepts + Advanced Topics
Apr 18	GAN Generative Adversarial Nets, NIPS'14 MaskGAN: Better Text Generation via Filling in the ___, ICLR'18 Optional: Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks, ICLR'16 SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient, AAAI'17 Adversarial Generation of Natural Language, ACL Representation Learning Workshop'17s
Apr 20	Variational Auto-Encoder Auto-Encoding Variational Bayes Variational Autoencoders Explained Optional: Variational Inference: A Review for Statisticians Semi-Amortized Variational Autoencoders	Friday make-up
Apr 23	No Class
Apr 25	No Class
Apr 30	Reinforcement Learning Deep Reinforcement Learning for Dialogue Generation (EMNLP'16) A Deep Reinforced Model for Abstractive Summarization (ICLR'18) Optional: Sequence Level Training with Recurrent Neural Networks (ICLR'16) DCN+: MIXED OBJECTIVE AND DEEP RESIDUAL COATTENTION FOR QUESTION ANSWERING (ICLR'18) Ranking Sentences for Extractive Summarization with Reinforcement Learning (Arxiv'18)	Project Proposal Due Advanced Topics
May 2	Attention Convolutional and multi-hop attention Attention is all you need Optional: QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension	The first paper review submission
May 7	No Class
May 9	Deep Networks ImageNet Classification with Deep Convolutional Neural Networks Deep Residual Learning for Image Recognition Neural Architectures for Named Entity Recognition Optional: Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
May 11	Sequence2Sequence Sequence to sequence learning with neural networks Pointer networks CTC speech recognition sequence modeling	Friday make-up
May 14	Parsing A Fast and Accurate Dependency Parser using Neural Networks Transition-Based Dependency Parsing with Stack Long Short-Term Memory DEEP BIAFFINE ATTENTION FOR NEURAL DEPENDENCY PARSING
May 16	Dialog How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation (EMNLP'16) Towards an Automatic Turing Test: Learning to Evaluate Dialogue Responses A Neural Network Approach to Context-Sensitive Generation of Conversational Responses Adversarial Learning for Neural Dialogue Generation
May 21	Meta Learning Model-agnostic meta-learning for fast adaptation of deep networks Meta-learning with memory-augmented neural networks Learning to learn by gradient descent by gradient descent Optional: Building machines that learn and think like people
May 23	Capsule network Dynamic Routing Between Capsules Capsule Network Performance on Complex Data Optional: Matrix Capsules with EM routing Transforming auto-encoders Untangling invariant object recognition Zero-Shot Learning Zero-Shot Learning - A Comprehensive Evaluation of the Good, the Bad and the Ugly	The second paper review submission
May 28	Memorial Day
May 30	Transfer Learning How transferable are features in deep neural networks? Optional: How Transferable are Neural Networks in NLP Applications?
June 4	Project Presentation
June 6	Project Presentation
June 8	Project Presentation Overflow	June 11 as the backup
June 13	Project Final Report Due