Search Results for author:
Found 16 papers, 1 papers with code
Cyber-Security Knowledge Graph Generation by Hierarchical Nonnegative Matrix Factorization
One of the challenges in constructing a KG from scientific literature is the extraction of ontology from unstructured text.
Interactive Distillation of Large Single-Topic Corpora of Scientific Papers
Given a small initial "core" corpus of papers, we build a citation network of documents.
MalwareDNA: Simultaneous Classification of Malware, Malware Families, and Novel Malware
Here we introduce and showcase preliminary capabilities of a new method that can perform precise identification of novel malware families, while also unifying the capability for malware/benign-ware classification and malware family classification into a single framework.
Robust Adversarial Defense by Tensor Factorization
This study underscores the potential of integrating tensorization and low-rank decomposition as a robust defense against adversarial attacks in machine learning.
Matrix Diagonalization as a Board Game: Teaching an Eigensolver the Fastest Path to Solution
Matrix diagonalization is at the cornerstone of numerous fields of scientific computing.
SeNMFk-SPLIT: Large Corpora Topic Modeling by Semantic Non-negative Matrix Factorization with Automatic Model Selection
As the amount of text data continues to grow, topic modeling is serving an important role in understanding the content hidden by the overwhelming quantity of documents.
FedSPLIT: One-Shot Federated Recommendation System Based on Non-negative Joint Matrix Factorization and Knowledge Distillation
Non-negative matrix factorization (NMF) with missing-value completion is a well-known effective Collaborative Filtering (CF) method used to provide personalized user recommendations.
Distributed Out-of-Memory NMF on CPU/GPU Architectures
In this work, we extend NMFk by adding support for dense and sparse matrix operation on multi-node, multi-GPU systems.
Integrating Deep Learning and Augmented Reality to Enhance Situational Awareness in Firefighting Environments
We present a new four-pronged approach to build firefighter's situational awareness for the first time in the literature.
A deep Q-Learning based Path Planning and Navigation System for Firefighting Environments
Live fire creates a dynamic, rapidly changing environment that presents a worthy challenge for deep learning and artificial intelligence methodologies to assist firefighters with scene comprehension in maintaining their situational awareness, tracking and relay of important features necessary for key decisions as they tackle these catastrophic events.
An embedded deep learning system for augmented reality in firefighting applications
Firefighting is a dynamic activity, in which numerous operations occur simultaneously.
Distributed Non-Negative Tensor Train Decomposition
Tensor train (TT) is a state-of-the-art tensor network introduced for factorization of high-dimensional tensors.
A Novel Indoor Positioning System for unprepared firefighting scenarios
Situational awareness and Indoor location tracking for firefighters is one of the tasks with paramount importance in search and rescue operations.
Diagram Image Retrieval using Sketch-Based Deep Learning and Transfer Learning
We then use our small set of manually labeled patent diagram images via transfer learning to adapt the image search from sketches of natural images to diagrams.
Learning Spatial Relationships between Samples of Patent Image Shapes
Binary image based classification and retrieval of documents of an intellectual nature is a very challenging problem.
A Deep Learning Framework for Detection of Targets in Thermal Images to Improve Firefighting
Intelligent detection and processing capabilities can be instrumental to improving the safety, efficiency, and successful completion of rescue missions conducted by firefighters in emergency first response settings.
