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Learning based approaches to achieve better statistics in Big Data
(2023-04-28)
Statistics in Big data has multiple applications. There are industrial systems that depend on quick and accurate insights into possible anomalies and irregularities on a large scale, for them to take better business ...
All You Need is Tensor Decomposition: A Better Understanding of Sparse Tensors
(2023-04-26)
Tensor is widely employed in data sciences to represent multi-dimensional information. Due to the low-rank nature of many tensors in the real world, predicting the unobserved entries of a partially observed tensor has ...
A Geospatial Approach to Preserving Location Privacy
(2023-04-26)
Sharing true locations of users has become a basic requirement for accessing Location-based
services (LBS) on a wide range of web and mobile applications. LBS require users
to provide their current location for service ...
From Edge to Equipment: Design and Implementation of a Machine-Learning-Enabled Smart Manufacturing System
(2023-04-27)
In smart manufacturing, data management systems are built with a multi-layer architecture, in which the most significant layers are the edge and cloud layers. The edge layer, not surprisingly, renders support to data ...
A Mobile Augmented Reality Assistant via Deep Learning and Lidar for the Visually Impaired and Blind
(2023-04-26)
Visually impaired and blind (VIB) people often face additional difficulties in their daily lives due to their lack of access to visual information, which reduces their quality of life. Due to their vision problems, it is ...
Use and Misuse of the Power Side Channel in Additive Manufacturing Security
(2023-05-02)
Additive Manufacturing (AM) is growing rapidly as an industry, particularly into the production of functional, safety-critical parts. AM Security has accordingly become a key research area for the technology, as sabotage ...
A Study of Adversarial Attacks on Machine Learning-based Fake News Detection Systems
(2023-05-04)
Due to the increased use and reliance on social media, fake news has become a significant problem that can cause great harm to individuals. Because of the dangerousness of fake news, techniques must be developed to detect ...
On the Adversarial Robustness of Machine Learning Models on Multi-Graph Scenarios
(2023-07-27)
In this work, we study the the task of graph matching under several scenarios in an adversarial context.
Despite achieving remarkable performance, deep learning based graph matching still suffers from harassment caused
by ...
A Research Framework for Asynchronous Adversarial Multi-Player Games with Human Player GUI and AI Gym
(2023-07-27)
The primary contribution of this thesis is to describe the design and development of a research framework to support complex, real-time asynchronous multi-agent simulations with both homogeneous as well as heterogeneous ...
A Framework Supporting Human-AI Adversarial Authorship: The Analysis of User Frustration to Improve System Efficiency
(2023-08-03)
Writing style can be traced back to a specific author with the use of authorship attribution techniques. These techniques use machine learning algorithms to classify the authors. This document discusses research focused ...