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08/06/2023
The Facebook Algorithm's Active Role in Climate Advertisement Delivery
Communication strongly influences attitudes on climate change. Within sp...
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04/11/2023
Program Comprehension Does Not Primarily Rely On the Language Centers of the Human Brain
Our goal is to identify brain regions involved in comprehending computer...
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11/21/2022
CLAWSAT: Towards Both Robust and Accurate Code Models
We integrate contrastive learning (CL) with adversarial learning to co-o...
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08/05/2021
Using a Collated Cybersecurity Dataset for Machine Learning and Artificial Intelligence
Artificial Intelligence (AI) and Machine Learning (ML) algorithms can su...
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06/25/2021
Fostering Diversity in Spatial Evolutionary Generative Adversarial Networks
Generative adversary networks (GANs) suffer from training pathologies su...
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04/27/2021
Proceedings - AI/ML for Cybersecurity: Challenges, Solutions, and Novel Ideas at SIAM Data Mining 2021
Malicious cyber activity is ubiquitous and its harmful effects have dram...
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04/23/2021
Automating Cyber Threat Hunting Using NLP, Automated Query Generation, and Genetic Perturbation
Scaling the cyber hunt problem poses several key technical challenges. D...
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03/18/2021
Generating Adversarial Computer Programs using Optimized Obfuscations
Machine learning (ML) models that learn and predict properties of comput...
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02/10/2021
Signal Propagation in a Gradient-Based and Evolutionary Learning System
Generative adversarial networks (GANs) exhibit training pathologies that...
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10/01/2020
BRON – Linking Attack Tactics, Techniques, and Patterns with Defensive Weaknesses, Vulnerabilities and Affected Platform Configurations
Many public sources of cyber threat and vulnerability information exist ...
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09/28/2020
STRATA: Building Robustness with a Simple Method for Generating Black-box Adversarial Attacks for Models of Code
Adversarial examples are imperceptible perturbations in the input to a n...
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08/03/2020
Analyzing the Components of Distributed Coevolutionary GAN Training
Distributed coevolutionary Generative Adversarial Network (GAN) training...
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04/08/2020
Dependency-Based Neural Representations for Classifying Lines of Programs
We investigate the problem of classifying a line of program as containin...
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04/07/2020
Data Dieting in GAN Training
We investigate training Generative Adversarial Networks, GANs, with less...
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04/07/2020
Adversarial Genetic Programming for Cyber Security: A Rising Application Domain Where GP Matters
Cyber security adversaries and engagements are ubiquitous and ceaseless....
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05/29/2019
Spatial Evolutionary Generative Adversarial Networks
Generative adversary networks (GANs) suffer from training pathologies su...
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02/19/2019
There are No Bit Parts for Sign Bits in Black-Box Attacks
Machine learning models are vulnerable to adversarial examples. In this ...
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12/14/2018
Using Detailed Access Trajectories for Learning Behavior Analysis
Student learning activity in MOOCs can be viewed from multiple perspecti...
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12/12/2018
Transfer Learning using Representation Learning in Massive Online Open Courses
In MOOCs predictive models of student behavior support many aspects of l...
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12/12/2018
Transfer Learning using Representation Learning in Massive Open Online Courses
In a Massive Open Online Course (MOOC), predictive models of student beh...
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11/30/2018
Lipizzaner: A System That Scales Robust Generative Adversarial Network Training
GANs are difficult to train due to convergence pathologies such as mode ...
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11/14/2018
Multivariate Time-series Similarity Assessment via Unsupervised Representation Learning and Stratified Locality Sensitive Hashing: Application to Early Acute Hypotensive Episod
Timely prediction of clinically critical events in Intensive Care Unit (...
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10/03/2018
AST-Based Deep Learning for Detecting Malicious PowerShell
With the celebrated success of deep learning, some attempts to develop e...
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07/21/2018
Towards Distributed Coevolutionary GANs
Generative Adversarial Networks (GANs) have become one of the dominant m...
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05/15/2018
On the Application of Danskin's Theorem to Derivative-Free Minimax Optimization
Motivated by Danskin's theorem, gradient-based methods have been applied...
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05/09/2018
On Visual Hallmarks of Robustness to Adversarial Malware
A central challenge of adversarial learning is to interpret the resultin...
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04/27/2018
Approximating Nash Equilibria for Black-Box Games: A Bayesian Optimization Approach
Game theory has emerged as a powerful framework for modeling a large ran...
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01/09/2018
Adversarial Deep Learning for Robust Detection of Binary Encoded Malware
Malware is constantly adapting in order to avoid detection. Model based ...
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07/27/2010
Computational Complexity Analysis of Simple Genetic Programming On Two Problems Modeling Isolated Program Semantics
Analyzing the computational complexity of evolutionary algorithms for bi...
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02/07/2007