Communication strongly influences attitudes on climate change. Within
sp...
Artificial Intelligence (AI) and Machine Learning (ML) algorithms can su...
Generative adversary networks (GANs) suffer from training pathologies su...
Malicious cyber activity is ubiquitous and its harmful effects have dram...
Scaling the cyber hunt problem poses several key technical challenges.
D...
Many public sources of cyber threat and vulnerability information exist ...
Distributed coevolutionary Generative Adversarial Network (GAN) training...
Generative adversarial networks (GANs) are widely used to learn generati...
We investigate training Generative Adversarial Networks, GANs, with less...
Cyber security adversaries and engagements are ubiquitous and ceaseless....
Generative Adversarial Networks (GANs) are popular tools for generative
...
Generative adversary networks (GANs) suffer from training pathologies su...
Student learning activity in MOOCs can be viewed from multiple perspecti...
In MOOCs predictive models of student behavior support many aspects of
l...
In a Massive Open Online Course (MOOC), predictive models of student beh...
GANs are difficult to train due to convergence pathologies such as mode ...
Generative Adversarial Networks (GANs) have become one of the dominant
m...
Motivated by Danskin's theorem, gradient-based methods have been applied...
A central challenge of adversarial learning is to interpret the resultin...
Game theory has emerged as a powerful framework for modeling a large ran...
Malware is constantly adapting in order to avoid detection. Model based
...
Grammatical Evolution (GE) is a population-based evolutionary algorithm,...