23 citations · 50 across the 8 of their papers we have counts for
9 papers
The Chess Transformer: Mastering Play using Generative Language Models
David Noever, Matt Ciolino, Josh Kalin
This work demonstrates that natural language transformers can support more generic strategic modeling, particularly for text-archived games. In addition to learning natural languag…
Black Box to White Box: Discover Model Characteristics Based on Strategic Probing
Josh Kalin, Matthew Ciolino, David Noever +1
In Machine Learning, White Box Adversarial Attacks rely on knowing underlying knowledge about the model attributes. This works focuses on discovering to distrinct pieces of model i…
The Go Transformer: Natural Language Modeling for Game Play
Matthew Ciolino, David Noever, Josh Kalin
This work applies natural language modeling to generate plausible strategic moves in the ancient game of Go. We train the Generative Pretrained Transformer (GPT-2) to mimic the sty…
Systematic Attack Surface Reduction For Deployed Sentiment Analysis Models
Josh Kalin, David Noever, Gerry Dozier
This work proposes a structured approach to baselining a model, identifying attack vectors, and securing the machine learning models after deployment. This method for securing each…
Knife and Threat Detectors
David A. Noever, Sam E. Miller Noever
Despite rapid advances in image-based machine learning, the threat identification of a knife wielding attacker has not garnered substantial academic attention. This relative resear…
The Enron Corpus: Where the Email Bodies are Buried?
David Noever
To probe the largest public-domain email database for indicators of fraud, we apply machine learning and accomplish four investigative tasks. First, we identify persons of interest…