4 citations · 10 across the 7 of their papers we have counts for
7 papers
Prediction of Runtime Parameters of Parallel Chemistry Applications via Active and Generative Learning
Tanzila Tabassum, Omer Subasi, Ajay Panyala +5
In this work, we develop two main Machine Learning based approaches to predict the runtime parameters of highly scalable parallel chemistry computations.These approaches employ act…
Guiding Application Users via Estimation of Computational Resources for Massively Parallel Chemistry Computations
Tanzila Tabassum, Omer Subasi, Ajay Panyala +6
In this work, we develop machine learning (ML) based strategies to predict resources (costs) required for massively parallel chemistry computations, such as coupled-cluster methods…
A Critical Assessment of Interpretable and Explainable Machine Learning for Intrusion Detection
Omer Subasi, Johnathan Cree, Joseph Manzano +1
There has been a large number of studies in interpretable and explainable ML for cybersecurity, in particular, for intrusion detection. Many of these studies have significant amoun…
The Landscape of Modern Machine Learning: A Review of Machine, Distributed and Federated Learning
Omer Subasi, Oceane Bel, Joseph Manzano +1
With the advance of the powerful heterogeneous, parallel and distributed computing systems and ever increasing immense amount of data, machine learning has become an indispensable…
Toward Automated Quantum Variational Machine Learning
Omer Subasi
In this work, we address the problem of automating quantum variational machine learning. We develop a multi-locality parallelizable search algorithm, called MUSE, to find the initi…
The Impact of Logical Errors on Quantum Algorithms
Omer Subasi, Sriram Krishnamoorthy
In this work, we explore the impact of logical stochastic Pauli and coherent Z-rotation errors on quantum algorithms. We evaluate six canonical quantum algorithms' intrinsic resili…
Denial-of-Service Attack Detection via Differential Analysis of Generalized Entropy Progressions
Omer Subasi, Joseph Manzano, Kevin Barker
Denial-of-Service (DoS) attacks are one of the most common and consequential cyber attacks in computer networks. While existing research offers a plethora of detection methods, the…