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Personalization and Data Relation Exploration using Predictive Analytics for the Production and Distributed Analysis System (PanDA)
(2016-08-26)
Efficient data distribution among computing centers is one of the biggest challenges in large-scale scientific distributed computing systems. Such data distribution issues include: i) the rational utilization of storage ...
ApproxML: Efficient Approximate Ad-Hoc ML Models Through Materialization and Reuse
(2019-12-10)
Machine Learning (ML) has become an essential tool in answering complex predictive analytic queries. Model building for large scale datasets is one of the most time-consuming parts of the data science pipeline. Often data ...
Classification of Factual and Non-Factual Statements Using Adversarially Trained LSTM Networks
(2020-06-08)
Being able to determine which statements are factual and therefore likely candidates for further verification is a key value-add in any automated fact-checking system. For this task, it has been shown that LSTMs outperform ...
Convex and Non-convex Optimization Methods for Machine Learning
(2019-08-01)
This dissertation is concerned with modeling fundamental and challenging machine learning tasks as convex/non-convex optimization problems and designing a mechanism that could solve them in a cost and time-effective manner. ...
Deep Learning for Recognition of Objects, Activities, Faces, and Spatio-Temporal Patterns
A popular method in machine learning is Convolutional Neural Network (CNN). CNN had was of high interest to the research community in the 1990s, but after that its popularity receded compared to the Support Vector Machine ...
LARGE-SCALE DEEP LEARNING WITH APPLICATION IN MEDICAL IMAGING AND BIO-INFORMATICS
(2018-11-27)
With the recent advancement of the deep learning technology in the artificial intelligence area, nowadays people's lives have been drastically changed. However, the success of deep learning technology mostly relies on ...
MACHINE LEARNING BASED DATACENTER MONITORING FRAMEWORK
(2016-12-09)
Monitoring the health of large data centers is a major concern with the ever-increasing demand of grid/cloud computing and the higher need of computational power. In a High Performance Computing (HPC) environment, the need ...
Integrative Approaches for Large-scale Biomedical Data Analysis
(2016-12-07)
Advancement of the Next Generation Sequencing (NGS), also known as the High Throughput Sequencing (HTS) technologies allow researchers investigate genome, transcriptome, or epigenome of any organism from any perspective, ...
COMPARISON OF MACHINE LEARNING ALGORITHMS IN SUGGESTING CANDIDATE EDGES TO CONSTRUCT A QUERY ON HETEROGENEOUS GRAPHS
(2016-05-11)
Querying graph data can be difficult as it requires the user to have knowledge of the underlying schema and the query language. Visual query builders allow users to formulate the intended query by drawing nodes and edges ...
DWRELU : DOUBLE WEIGHTED RECTIFIER LINEAR UNIT AN ACTIVATION FUNCTION WITH TRAINABLE SCALING PARAMETER
(2018-11-14)
Deep Neural Network have become very popular for computer vision application in recent years. At the same time, it remains important to understand the different implementation choices that need to be made when designing a ...