Overview
Syllabus
Intro
Outline
An Example Prediction Problem: Sentiment Classification
Continuous Bag of Words (CBOW)
Deep CBOW
Why Bag of n-grams?
What Problems
Neural Sequence Models
Definition of Convolution
Intuitive Understanding
Priori Entailed by CNNS
Concept: 2d Convolution
Concept: Stride
Concept: Padding
Three Types of Convolutions
Concept: Multiple Filters
Concept: Pooling
Overview of the Architecture
Embedding Layer
Conv. Layer
Pooling Layer
Output Layer
Dynamic Filter CNN (e.g. Brabandere et al. 2016)
CNN Applications
NLP (Almost) from Scratch (Collobert et al. 2011)
CNN-RNN-CRF for Tagging (Ma et al. 2016) . A classic framework and de-facto standard for
Why Structured Convolution?
Understand the design philosophy of a model
Structural Bias
component entail?
Taught by
Graham Neubig