53 citations · 55 across the 3 of their papers we have counts for
3 papers
cs.LG2020★ 2 cited
Playing to Learn Better: Repeated Games for Adversarial Learning with Multiple Classifiers
Prithviraj Dasgupta, Joseph B. Collins, Michael McCarrick
We consider the problem of prediction by a machine learning algorithm, called learner, within an adversarial learning setting. The learner's task is to correctly predict the class…
cs.CR2019★ 53 cited
A Survey of Game Theoretic Approaches for Adversarial Machine Learning in Cybersecurity Tasks
Prithviraj Dasgupta, Joseph B. Collins
Machine learning techniques are currently used extensively for automating various cybersecurity tasks. Most of these techniques utilize supervised learning algorithms that rely on…
cs.MA2012
A Multi-Agent Prediction Market based on Partially Observable Stochastic Game
Janyl Jumadinova, Prithviraj Dasgupta
We present a novel, game theoretic representation of a multi-agent prediction market using a partially observable stochastic game with information (POSGI). We then describe a corre…