Introduction to and Advances in Deep Learning

Organizers: Z. Tom Hu, Yuting Ye

Please direct questions to {zyhu95, yeyt} AT berkeley DOT edu

This semester (spring 2019), we will be hosting a group study on deep learning at Friday 3 - 4:30pm in Evans 443 (The first week will be at Evans 422). This is a fast-paced and demanding study group which covers both fundementals of deep learning and recent advances. We highly encourage everyone to read the related materials before the group study.

Everyone is welcomed to sit in. However, due to our fast pace and limited room capacity, we make the following two remarks:

  • If the room is too full and we’re running out of space, we would ask that sitting-in guests please allow our lab members to sit.
  • Presenter is not obligated to answer any sitting-in guest’s questions during his or her presentation for smoothness.

Below is the tentative schedule we proposed for SPRING 2019 semester.

Date Content Speaker Resource
Feb 22 Introduction, Fully Connected Network, Back-Prop, SGD, General Tricks in Training Tom ref1, ref2
Mar 1 Convolutional Neural Network (CNN) Tom ref1, ref2
Mar 7 Generative Models I: Introduction, Autoencoder Yuting ref1, ref2
Mar 15 Generative Models II: Variational Autoencoder, Adversarial Variational Bayes Yuting ref1, ref2
Mar 22 Generative Models III: Variational Autoencoder Applications Yuting ref1
Apr 12 Generative Models IV: Generative Adversarial Nets Yuting [ref1], [ref2]
Apr 19 Recurrent Neural Network (RNN) Tom ref1, ref2
May 3 Applications of RNN to NLP I: preliminaries, word2vec, language model Tom ref1
May 10 Applications of RNN to NLP II: machine translations, seq2seq, attention Tom ref1
May 17 Deep Learning in Recommender Systems Guest ref1