Sleep apnea is a sleep related disorder that significantly affects the population.
Polysomnography, the gold standard, is expensive, inaccessible, uncomfortable and an …

Since it can effectively address the problem of sparsity and cold start of collaborative
filtering, knowledge graph (KG) is widely studied and employed as side information in the …

A fundamental operation in many vision tasks, including motion understanding, stereopsis,
visual odometry, or invariant recognition, is establishing correspondences between images …

Getting a good feature representation of data is paramount for Human Activity Recognition
(HAR) using wearable sensors. An increasing number of feature learning approaches—in …

This paper proposes two one-dimensional (1D) convolutional neural networks (CNNs) for
predicting dominant wind speed and direction for the temporal wind dataset. The proposed …

In this paper, we present methods in deep multimodal learning for fusing speech and visual
modalities for Audio-Visual Automatic Speech Recognition (AV-ASR). First, we study an …

Recent developments have demonstrated the capacity of restricted Boltzmann machines
(RBM) to be powerful generative models, able to extract useful features from input data or …

Machine learning can provide deep insights into data, allowing machines to make high-
quality predictions and having been widely used in real-world applications, such as text …

We present a new deep network layer called``Dynamic Convolutional Layer" which is a
generalization of the convolutional layer. The conventional convolutional layer uses filters …

Massive open online courses (MOOCs) are dedicated to providing learners with large-scale
and open-access boutique courses. Recently, the course recommendation algorithm in …