Publications

Results 1–25 of 26
Date Inputs. Currently set to enter a start and end date.
Current Filters Clear all
  • Remove author filter×
Publication Type Year

Going Beyond Signature Malware Detection by Learning Behaviors

Malware Technical Exchange Meeting

Nicholas T. Johnson, Eva Domschot, Kanad Khanna, William Philip Kegelmeyer, Christopher Lamb, Ramyaa Ramyaa, Michael Reed Smith, Stephen Joseph Verzi, Xin Zhou, Armida J. Carbajal, Bridget Haus, Joey Burton Ingram

Conference Presentation – 2021 Conference Presentation 2021

Mind the Gap: On Bridging the Semantic Gap Between Machine Learning and Malware Analysis

13th ACM Workshop on Artificial Intelligence and Security

Michael Reed Smith, Nicholas T. Johnson, Joey Burton Ingram, Armida J. Carbajal, Bridget Irene Haus, Eva Domschot, Ramyaa Ramyaa, Christopher Lamb, Stephen Joseph Verzi, William Philip Kegelmeyer

https://www.osti.gov/search/identifier:1831009

Conference Presentation – 2020 Conference Presentation 2020

MalGen: On Bridging the Semantic Gap between Machine Learning and Malware Analysis

Sandia Machine Learning and Deep Learning Workshop

Michael Reed Smith, Armida J. Carbajal, Eva Domschot, Bridget Irene Haus, Joey Burton Ingram, Nicholas T. Johnson, William Philip Kegelmeyer, Christopher Lamb, Ramyaa Ramyaa, Stephen Joseph Verzi

https://www.osti.gov/search/identifier:1811972

Conference Paper – 2020 Conference Paper 2020

Mind the Gap: On Bridging the Semantic Gap between Machine Learning and Malware Analysis

13th ACM Workshop on Artificial Intelligence and Security

Michael Reed Smith, Nicholas T. Johnson, Joey Burton Ingram, Armida J. Carbajal, Bridget Irene Haus, Eva Domschot, Ramyaa Ramyaa, Christopher Lamb, Stephen Joseph Verzi, William Philip Kegelmeyer

https://www.osti.gov/search/identifier:1807188

Conference Paper – 2020 Conference Paper 2020

Mind the Gap: On Bridging the Semantic Gap between Machine Learning and Information Security

The ACM Conference on Computer and Communications Security

Michael Reed Smith, Nicholas T. Johnson, Joey Burton Ingram, Armida J. Carbajal, Ramyaa Ramyaa, Evelyn Domschot, Christopher Lamb, Stephen Joseph Verzi, William Philip Kegelmeyer

https://www.osti.gov/search/identifier:1782493

Conference Paper – 2020 Conference Paper 2020

In-Situ Machine Learning for Intelligent Data Capture on Exascale Platforms

Artificial Intelligence for Robust Engineering & Science

Warren Leon Davis IV, Timothy Malcolm Shead, Hemanth Kolla, Kevin Reed, William Philip Kegelmeyer, Gabriel ANUOLUWAPO Popoola

https://www.osti.gov/search/identifier:1762271

Presentation (non-conference) – 2020 Presentation (non-conference) 2020

The Potential of Integrated Machine Learning Algorithms for Tropical Cyclone Detection in Advanced Climate Modeling

American Geophysical Union Fall Conference 2019

Warren Leon Davis IV, Timothy M. Shead, Hemanth Kolla, Gabriel ANUOLUWAPO Popoola, William Philip Kegelmeyer, Aditya Konduri

https://www.osti.gov/search/identifier:1643419

Conference Paper – 2019 Conference Paper 2019

Data Analytics are Powerful -- Handle with Care

Chesapeake Large-Scale Analytics Conference

Jeremy D Wendt, William Philip Kegelmeyer, Ali Pinar, Timothy Malcolm Shead, Gary Joseph Saavedra, Cosmin Safta, Joseph Bertino

https://www.osti.gov/search/identifier:1642746

Conference Paper – 2019 Conference Paper 2019

In-Situ Machine Learning for Intelligent Data Capture on Exascale Platforms

2019 Cis Erb

Warren Leon Davis, Timothy Malcolm Shead, Hemanth Kolla, William Philip Kegelmeyer, Gabriel ANUOLUWAPO Popoola, Kevin Reed

https://www.osti.gov/search/identifier:1645860

Presentation (non-conference) – 2019 Presentation (non-conference) 2019

The Potential of In-Situ Machine Learning Algorithms for Tropical Cyclone Detection in Advanced Climate Modeling

American Geophysical Union Fall Meeting 2019

Warren Leon Davis, Kevin Reed, Timothy Malcolm Shead, Hemanth Kolla, Gabriel ANUOLUWAPO Popoola, William Philip Kegelmeyer, Aditya Konduri, Julia Ling

Abstract – 2019 Abstract 2019

A Framework for In-Situ Anomaly Detection in HPC Environments

Ldav 2019

Timothy Malcolm Shead, Daniel Dunlavy, Hemanth Kolla, Aditya Konduri, Gabriel ANUOLUWAPO Popoola, Warren Leon Davis, William Philip Kegelmeyer, Kevin Reed, Julia Ling

https://www.osti.gov/search/identifier:1640853

Conference Paper – 2019 Conference Paper 2019

Adverse Event Prediction Using Graph-Augmented Temporal Analysis: Final Report

Randolph Brost, Erin E. Carrier, Michelle Carroll, Katrina M. Groth, William Philip Kegelmeyer, Vitus J. Leung, Hamilton E. Link, Andrew John Patterson, Cynthia Ann Phillips, Samuel Richter, David G. Robinson, Andrea Staid, Diane M.-K. Woodbridge

https://www.osti.gov/search/identifier:1530166

SAND Report – 2018 SAND Report 2018

Embedding Python for In-Situ Analysis

Daniel Dunlavy, Timothy Malcolm Shead, Daniel Dunlavy, Aditya Konduri, Hemanth Kolla, Daniel Dunlavy, William Philip Kegelmeyer, Warren Leon Davis

https://www.osti.gov/search/identifier:1734473

SAND Report – 2018 SAND Report 2018

Anomaly detection in scientific data using joint statistical

ArXiv

Aditya Konduri, Hemanth Kolla, William Philip Kegelmeyer, Timothy Malcolm Shead, Julia Ling, Warren Leon Davis

https://www.osti.gov/search/identifier:1502456

Journal Article – 2018 Journal Article 2018

In-Situ Machine Learning for Intelligent Data Capture in HPC Simulations

CIS External Advisory Board Meeting

Warren Leon Davis, Daniel Dunlavy, William Philip Kegelmeyer, Hemanth Kolla, Aditya Konduri, Timothy Malcolm Shead, Kevin Reed

https://www.osti.gov/search/identifier:1524824

Conference Paper – 2018 Conference Paper 2018

Event Detection In Multi-variate Scientific Simulations Using Feature Anomaly Metrics

SIAM Conference on Parallel Processing for Scientific Computing (PP18)

Aditya Konduri, Hemanth Kolla, Julia Ling, William Philip Kegelmeyer, Daniel Dunlavy, Timothy Malcolm Shead, Warren Leon Davis

https://www.osti.gov/search/identifier:1499084

Conference Paper – 2018 Conference Paper 2018

Embedding Python for In-Situ Analysis

In Situ Infrastructures for Enabling Extreme-scale Analysis and Visualization

Timothy Malcolm Shead, Aditya Konduri, Hemanth Kolla, Daniel Dunlavy, William Philip Kegelmeyer

https://www.osti.gov/search/identifier:1467787

Conference Paper – 2017 Conference Paper 2017

Using Feature Importance Metrics to Detect Events of Interest in Scientific Computing Applications

Kdd 2017

Julia Ling, William Philip Kegelmeyer, Aditya Konduri, Hemanth Kolla, Kevin Reed, Timothy Malcolm Shead, Warren Leon Davis

https://www.osti.gov/search/identifier:1505710

Conference Paper – 2017 Conference Paper 2017

PANTHER: Trajectory Analysis

Mark Daniel Rintoul, Andrew T. Wilson, Christopher G. Valicka, William Philip Kegelmeyer, Timothy Malcolm Shead, Kristina Rodriguez Czuchlewski, Benjamin D. Newton

https://www.osti.gov/search/identifier:1221864

SAND Report – 2015 SAND Report 2015

Characterizing and Detecting Aircraft Identity and Diversion

The 19th Annual Signal & Image Sciences Workshop

William Philip Kegelmeyer, Timothy Malcolm Shead, Mark Daniel Rintoul, Andrew T. Wilson

https://www.osti.gov/search/identifier:1251131

Conference Paper – 2015 Conference Paper 2015

Machine Learning in the Presence of Adversarial Tampering, or, What To Do When Your Truth Data Lies?

ASCR Machine Learning for Scientific Discovery Workshop

William Philip Kegelmeyer, Timothy Malcolm Shead, Jonathan Crussell, David G. Robinson

Abstract – 2014 Abstract 2014

Advanced ALE Remeshing Methods in ALEGRA

CIS External Review

William Philip Kegelmeyer, Thomas E. Voth

Other Publication – 2013 Other Publication 2013

Multilinear algebra for analyzing data with multiple linkages

DOE Applied Mathematics Principal Investigators Meeting

Daniel Dunlavy, Tamara G. Kolda, William Philip Kegelmeyer

https://www.osti.gov/search/identifier:966593

Conference Paper – 2009 Conference Paper 2009

Tensor Decompositions for Analyzing Multi-link Graphs

SIAM Conference on Parallel Processing for Scientific Computing

Daniel Dunlavy, Tamara G. Kolda, William Philip Kegelmeyer

https://www.osti.gov/search/identifier:1145612

Conference Paper – 2008 Conference Paper 2008

Multilinear algebra for analyzing data with multiple linkages

Tamara G. Kolda, Daniel Dunlavy, William Philip Kegelmeyer

https://www.osti.gov/search/identifier:923081

SAND Report – 2006 SAND Report 2006
Document Title Type Year
Results 1–25 of 26