8 citations · 28 across the 20 of their papers we have counts for
24 papers
Patchfinder: Leveraging Visual Language Models for Accurate Information Retrieval using Model Uncertainty
Roman Colman, Minh Vu, Manish Bhattarai +4
For decades, corporations and governments have relied on scanned documents to record vast amounts of information. However, extracting this information is a slow and tedious process…
LoRID: Low-Rank Iterative Diffusion for Adversarial Purification
Geigh Zollicoffer, Minh Vu, Ben Nebgen +3
This work presents an information-theoretic examination of diffusion-based purification methods, the state-of-the-art adversarial defenses that utilize diffusion models to remove m…
LaFA: Latent Feature Attacks on Non-negative Matrix Factorization
Minh Vu, Ben Nebgen, Erik Skau +5
As Machine Learning (ML) applications rapidly grow, concerns about adversarial attacks compromising their reliability have gained significant attention. One unsupervised ML method…
Tensor Train Low-rank Approximation (TT-LoRA): Democratizing AI with Accelerated LLMs
Afia Anjum, Maksim E. Eren, Ismael Boureima +2
In recent years, Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide range of natural language processing (NLP) tasks, such as question-answering,…
Enhancing Code Translation in Language Models with Few-Shot Learning via Retrieval-Augmented Generation
Manish Bhattarai, Javier E. Santos, Shawn Jones +3
The advent of large language models (LLMs) has significantly advanced the field of code translation, enabling automated translation between programming languages. However, these mo…
Catch'em all: Classification of Rare, Prominent, and Novel Malware Families
Maksim E. Eren, Ryan Barron, Manish Bhattarai +5
National security is threatened by malware, which remains one of the most dangerous and costly cyber threats. As of last year, researchers reported 1.3 billion known malware specim…
Interactive Distillation of Large Single-Topic Corpora of Scientific Papers
Nicholas Solovyev, Ryan Barron, Manish Bhattarai +3
Highly specific datasets of scientific literature are important for both research and education. However, it is difficult to build such datasets at scale. A common approach is to b…
Semi-supervised Classification of Malware Families Under Extreme Class Imbalance via Hierarchical Non-Negative Matrix Factorization with Automatic Model Selection
Maksim E. Eren, Manish Bhattarai, Robert J. Joyce +3
Identification of the family to which a malware specimen belongs is essential in understanding the behavior of the malware and developing mitigation strategies. Solutions proposed…
MalwareDNA: Simultaneous Classification of Malware, Malware Families, and Novel Malware
Maksim E. Eren, Manish Bhattarai, Kim Rasmussen +2
Malware is one of the most dangerous and costly cyber threats to national security and a crucial factor in modern cyber-space. However, the adoption of machine learning (ML) based…
Robust Adversarial Defense by Tensor Factorization
Manish Bhattarai, Mehmet Cagri Kaymak, Ryan Barron +3
As machine learning techniques become increasingly prevalent in data analysis, the threat of adversarial attacks has surged, necessitating robust defense mechanisms. Among these de…
Matrix Diagonalization as a Board Game: Teaching an Eigensolver the Fastest Path to Solution
Phil Romero, Manish Bhattarai, Christian F. A. Negre +2
Matrix diagonalization is at the cornerstone of numerous fields of scientific computing. Diagonalizing a matrix to solve an eigenvalue problem requires a sequential path of iterati…
SeNMFk-SPLIT: Large Corpora Topic Modeling by Semantic Non-negative Matrix Factorization with Automatic Model Selection
Maksim E. Eren, Nick Solovyev, Manish Bhattarai +3
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. One popular…
Distributed Out-of-Memory SVD on CPU/GPU Architectures
Ismael Boureima, Manish Bhattarai, Maksim E. Eren +3
We propose an efficient, distributed, out-of-memory implementation of the truncated singular value decomposition (t-SVD) for heterogeneous (CPU+GPU) high performance computing (HPC…
FedSPLIT: One-Shot Federated Recommendation System Based on Non-negative Joint Matrix Factorization and Knowledge Distillation
Maksim E. Eren, Luke E. Richards, Manish Bhattarai +3
Non-negative matrix factorization (NMF) with missing-value completion is a well-known effective Collaborative Filtering (CF) method used to provide personalized user recommendation…
Distributed non-negative RESCAL with Automatic Model Selection for Exascale Data
Manish Bhattarai, Namita Kharat, Erik Skau +5
With the boom in the development of computer hardware and software, social media, IoT platforms, and communications, there has been an exponential growth in the volume of data prod…
Distributed Out-of-Memory NMF on CPU/GPU Architectures
Ismael Boureima, Manish Bhattarai, Maksim Eren +4
We propose an efficient distributed out-of-memory implementation of the Non-negative Matrix Factorization (NMF) algorithm for heterogeneous high-performance-computing (HPC) systems…
Integrating Deep Learning and Augmented Reality to Enhance Situational Awareness in Firefighting Environments
Manish Bhattarai
We present a new four-pronged approach to build firefighter's situational awareness for the first time in the literature. We construct a series of deep learning frameworks built on…
A deep Q-Learning based Path Planning and Navigation System for Firefighting Environments
Manish Bhattarai, Manel Martinez-Ramon
Live fire creates a dynamic, rapidly changing environment that presents a worthy challenge for deep learning and artificial intelligence methodologies to assist firefighters with s…
An embedded deep learning system for augmented reality in firefighting applications
Manish Bhattarai, Aura Rose Jensen-Curtis, Manel MartíNez-Ramón
Firefighting is a dynamic activity, in which numerous operations occur simultaneously. Maintaining situational awareness (i.e., knowledge of current conditions and activities at th…
A Novel Indoor Positioning System for unprepared firefighting scenarios
Vamsi Karthik Vadlamani, Manish Bhattarai, Meenu Ajith +1
Situational awareness and Indoor location tracking for firefighters is one of the tasks with paramount importance in search and rescue operations. For Indoor Positioning systems (I…
Distributed Non-Negative Tensor Train Decomposition
Manish Bhattarai, Gopinath Chennupati, Erik Skau +3
The era of exascale computing opens new venues for innovations and discoveries in many scientific, engineering, and commercial fields. However, with the exaflops also come the extr…
Learning Spatial Relationships between Samples of Patent Image Shapes
Juan Castorena, Manish Bhattarai, Diane Oyen
Binary image based classification and retrieval of documents of an intellectual nature is a very challenging problem. Variations in the binary image generation mechanisms which are…
Diagram Image Retrieval using Sketch-Based Deep Learning and Transfer Learning
Manish Bhattarai, Diane Oyen, Juan Castorena +2
Resolution of the complex problem of image retrieval for diagram images has yet to be reached. Deep learning methods continue to excel in the fields of object detection and image c…
A Deep Learning Framework for Detection of Targets in Thermal Images to Improve Firefighting
Manish Bhattarai, Manel Martínez-Ramón
Intelligent detection and processing capabilities can be instrumental to improving the safety, efficiency, and successful completion of rescue missions conducted by firefighters in…