Knowledge graphs represent factual knowledge about the world as relationships between concepts and are critical for intelligent decision making in enterprise applications. New knowledge is inferred from the existing facts ...

Machine-learning models have been recently developed in various computer vision applications, such as image detention, segmentation and so on. Models are often trained based on data that present various levels of accuracy, ...

Channel pruning is an effective technique to reduce the size of Convolutional Neural Networks (CNNs). A decisive part of any pruning algorithm is its saliency metric. We propose different techniques to improve saliency ...

Internet of Things (IoT) applications can be built from a number of heterogeneous services provided by a range of devices, which are potentially resource constrained and/or mobile. These device characteristics can lead to ...

My thesis focuses on two key challenges in Recommender System: the Cold Start Problem and Data Poisoning attacks within the user-clustering framework. We explored utilizing user clustering to address the Cold Start Problem, ...