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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.
Network of unmanned vehicles, are poised to be the next giant leap of technology. Such systems are already being used by the defense and law enforcement agencies. The US DoD and some very large private corporations are spending large...
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...
Query rewriting (QR) is a critical component in dialogue systems for reducing frictions caused by systematic errors or user ambiguity. When there is an entity error, it imposes extra difficulty for a dialogue system to produce...
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...
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...
Many of today's underwater vehicles have a limited set of pre-planned behaviors that are of varying utility. This is due, in part, to very low underwater communication rates and difficulties observing the vehicle's underwater behavior...
Over the years, the storage substrate of operating systems has evolved with changing storage devices and workloads [2, 6, 7, 8, 12, 15, 18, 26, 29, 33, 34, 35, 39, 41, 42, 44, 47, 48, 54]. Both academia and industry have devoted...
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....
With the popularity of microprocessors and scale-out system architectures, many large-scale high-performance computing (HPC) systems are built from a collection of compute servers, with an identical set of resources such as CPU, memory, ...
There is a growing demand for technology that can sense people and objects without imposing excessive overhead. Traditional solutions usually require people to wear additional devices on their bodies and install cumbersome sensors on...
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...
The revolution in next-generation DNA sequencing technologies is leading to explosive data growth in genomics, posing a significant challenge to the computing infrastructure and software algorithms for genomics analysis. Various big data...
Sustainability research of the environment depends on accurate land cover information over large areas. Even with the increased number of satellite systems and sensors acquiring data with improved spectral, spatial, radiometric and...
Low-rank matrix approximation is extremely useful in the analysis of data that arises in scientific computing, engineering applications, and data science. However, as data sizes grow, traditional low-rank matrix approximation methods, ...
The legacy storage data path is largely structured in black-box layers and has four major limitations: (1) functional redundancies across layers, (2) poor cross-layer coordination and data tracking, (3) presupposition of high-latency...
This dissertation is centered on indexing, searching, and mining methods for large-scale and high-dimensional visual data. While the processing to such data has been widely acknowledged to be difficult, the problem becomes more serious...
In this dissertation, I explore different types of applications in the area of applied machine learning, time series analysis, and prediction. Time series forecasting is a fundamental task in machine learning and data mining. It is an...
Graph-structured data widely exists in the real world, including biomedical, e-commerce, and social areas. The graph-structured data contains objects and relationships among them, which refer to nodes and edges in the graph, respectively...
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.
