stat441w18/Convolutional Neural Networks for Sentence Classification: Difference between revisions
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=== Model Regularization === | === Model Regularization === | ||
=== Datasets and Experimental Setup === | |||
===== Hyperparameters and Training ===== | |||
===== Pre-trained Word Vectors ===== | |||
===== Model Variations ===== | |||
= Training and Results = | = Training and Results = | ||
Revision as of 16:49, 4 March 2018
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].