- Deep Learning Reading Group: Skip-Thought Vectors - Nov 17, 2016.
Skip-thought vectors take inspiration from Word2Vec skip-gram and attempt to extend it to sentences, and are created using an encoder-decoder model. Read on for an overview of the paper.
Deep Learning, Lab41, Natural Language Processing, Neural Networks, word2vec
- Deep Learning Reading Group: SqueezeNet - Sep 29, 2016.
This paper introduces a small CNN architecture called “SqueezeNet” that achieves AlexNet-level accuracy on ImageNet with 50x fewer parameters.
Compression, Deep Learning, Lab41, Machine Learning, Neural Networks
- Deep Learning Reading Group: Deep Residual Learning for Image Recognition - Sep 22, 2016.
Published in 2015, today's paper offers a new architecture for Convolution Networks, one which has since become a staple in neural network implementation. Read all about it here.
Academics, Convolutional Neural Networks, Deep Learning, Image Recognition, Lab41, Machine Learning, Neural Networks
- Deep Learning Reading Group: Deep Networks with Stochastic Depth - Sep 8, 2016.
An concise overview of a recent paper which introduces a new way to perturb networks during training in order to improve their performance, stochastic depth networks.
Academics, Deep Learning, Lab41, Neural Networks
- 9 Must-Have Datasets for Investigating Recommender Systems - Feb 11, 2016.
Gain some insight into a variety of useful datasets for recommender systems, including data descriptions, appropriate uses, and some practical comparison.
Datasets, Lab41, Recommender Systems
