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Some of the material in is restricted to members of the community. By logging in, you may be able to gain additional access to certain collections or items. If you have questions about access or logging in, please use the form on the Contact Page.
Malware has crippled computer systems, caused financial losses on the order of billions of dollars and denied access to services for millions of users worldwide. Detecting malware before it can cause any damage, therefore, is a...
With the recent advances in the field of Machine Learning, there have been several developments in modern power systems computations. Meanwhile, causality has also received a lot of recognition in various fields such as economics, social...
By removing as much as 90% or more of a deep neural network's (DNN's) parameters, a wide variety of pruning approaches not only allow for DNN compression but also increase generalization (model performance on test/unseen data). This...
Computer vision principles enable the analysis of fire, wind, and plume behavior from visual and infrared (IR) video as opposed to sparse measurements obtained with expensive instrumentation. Data that quantifies the transport of heat...
This thesis introduces in detail how we apply deep neural networks to solve several natural language processing problems, including Word Sense Disambiguation (WSD), word representation and knowledge-base completion. We apply...
The unique physical properties of nanoparticles depend on their sizes and shapes. Therefore, an ability to precisely control the size of nanoparticles and tune their morphology will allow scientists and engineers to modify their physical...
In numerous applications involving high dimensional data, certain subspace techniques such as principal components analysis (PCA) may be utilized in feature extraction. Often, PCA can reduce the dimensionality while retaining most of the...
Bayesian additive regression trees (BART) are a Bayesian machine learning tool for nonparametric function estimation, which has been shown to have outstanding performance in terms of variable selection and prediction accuracy. Unmodified...
Regression over circular response data requires special methods due to the periodic nature of this data type. In previous works, researchers tried to use the concept of projecting real-line distributions on unit circles or using...
Neural network based word embeddings have demonstrated outstanding results in a variety of tasks, and become a standard input for Natural Language Processing (NLP) related deep learning methods. Despite these representations are able to...
Clustering is a fundamental data mining tool that aims to divide data into groups of similar items. Intuition about clustering reflects the ideal case -- exact data sets endowed with flawless dissimilarity between individual instances....
Animals have demonstrated the capacity to traverse many complex unstructured terrains at high speeds by utilizing effective locomotion regimes. Motion in difficult and uncertain environments have only seen partial success on traditional...
Statistical data models based on the deep learning paradigm have shown remarkable performance in many domains, surpassing human performance in a set of tasks under restricted settings. However, the fundamental reasons enabling these...
As capacitors age, the likelihood of failure increases. Electrolytic capacitors typically fail when their electrolyte layers evaporate, resulting in an open-circuit fault which is minimally dangerous to other circuit components in the...
Predictive modeling can help researchers tackle challenges such as detection, prevention, and treatment for diseases with high mortality rates such as cardiovascular diseases. These diseases involve multiple risk factors that make...
Hurricanes cause significant property loss every year. A substantial part of that loss is due to the trees destroyed by the wind, which in turn block the roads and produce a large amount of debris. The debris not only can cause damage to...
This study is a preliminary exploration of adoption of generative adversarial network (GAN)-derived avatar healthcare providers (HCPs). To our knowledge, GAN-derived avatars as de facto HCPs have not been investigated in relation to user...
Mental or emotional states are an important part of the information that can be observed from the speakers or writers of many discourses. On social media, people often share their emotional responses to events, stories, news, etc. The...
As the push for autonomous systems gains momentum, there has been a shift from automated to semi-autonomous systems, and current and future applications of artificial intelligence will revolve around the development of autonomous systems...
Some of the material in is restricted to members of the community. By logging in, you may be able to gain additional access to certain collections or items. If you have questions about access or logging in, please use the form on the Contact Page.
