stat441w18/Convolutional Neural Networks for Sentence Classification

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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

Training and Results

Criticisms

More Formulations/New Concepts

Conclusion

Source