200 citations · 221 across the 2 of their papers we have counts for
4 papers
Large-Scale User Modeling with Recurrent Neural Networks for Music Discovery on Multiple Time Scales
Cedric De Boom, Rohan Agrawal, Samantha Hansen +5
The amount of content on online music streaming platforms is immense, and most users only access a tiny fraction of this content. Recommender systems are the application of choice…
Representation learning for very short texts using weighted word embedding aggregation
Cedric De Boom, Steven Van Canneyt, Thomas Demeester +1
Short text messages such as tweets are very noisy and sparse in their use of vocabulary. Traditional textual representations, such as tf-idf, have difficulty grasping the semantic…
Lazy Evaluation of Convolutional Filters
Sam Leroux, Steven Bohez, Cedric De Boom +5
In this paper we propose a technique which avoids the evaluation of certain convolutional filters in a deep neural network. This allows to trade-off the accuracy of a deep neural n…
Efficiency Evaluation of Character-level RNN Training Schedules
Cedric De Boom, Sam Leroux, Steven Bohez +3
We present four training and prediction schedules from the same character-level recurrent neural network. The efficiency of these schedules is tested in terms of model effectivenes…