stat441w18/Convolutional Neural Networks for Sentence Classification
Presented by
1. Ben Schwarz
2. Cameron Miller
3. Hamza Mirza
4. Pavle Mihajlovic
5. Terry Shi
6. Yitian Wu
7. Zekai Shao
Introduction
Model
Model Settings
Consider a sentence of length [math]\displaystyle{ n }[/math], represented by [math]\displaystyle{ \boldsymbol{x}_{1:n} }[/math]. Let [math]\displaystyle{ \boldsymbol{x}_i \in \mathbb{R}^k }[/math] be the [math]\displaystyle{ i }[/math]-th word in this sentence and [math]\displaystyle{ \oplus }[/math] be the concatenation operator. Thus,
[math]\displaystyle{ \boldsymbol{x}_{1:n} = \boldsymbol{x}_{1} \oplus \boldsymbol{x}_2 \oplus \dots \oplus \boldsymbol{x}_n }[/math].
Model Regularization
Datasets and Experimental Setup
Hyperparameters and Training
MR:
SST-1:
SST-2:
Subj:
TREC:
CR:
MPQA:
Pre-trained Word Vectors
Model Variations
CNN-rand:
CNN-static:
CNN-static:
CNN-non-static:
CNN-multichannel: