7 citations · 22 across the 12 of their papers we have counts for
4 papers · 1 filter
Continual Prediction of Notification Attendance with Classical and Deep Network Approaches
Kleomenis Katevas, Ilias Leontiadis, Martin Pielot +1
We investigate to what extent mobile use patterns can predict -- at the moment it is posted -- whether a notification will be clicked within the next 10 minutes. We use a data set…
Language and Noise Transfer in Speech Enhancement Generative Adversarial Network
Santiago Pascual, Maruchan Park, Joan Serrà +2
Speech enhancement deep learning systems usually require large amounts of training data to operate in broad conditions or real applications. This makes the adaptability of those sy…
Getting deep recommenders fit: Bloom embeddings for sparse binary input/output networks
Joan Serrà, Alexandros Karatzoglou
Recommendation algorithms that incorporate techniques from deep learning are becoming increasingly popular. Due to the structure of the data coming from recommendation domains (i.e…
Practical Processing of Mobile Sensor Data for Continual Deep Learning Predictions
Kleomenis Katevas, Ilias Leontiadis, Martin Pielot +1
We present a practical approach for processing mobile sensor time series data for continual deep learning predictions. The approach comprises data cleaning, normalization, capping,…