12 citations · 43 across the 22 of their papers we have counts for
30 papers
A Bayesian Correlated Equilibrium for Early Insider-Threat Detection
Javed M. Shah, Ian A. Kash, Natalie Parde
We model insider threat detection as a dynamic Bayesian game in which a platform coordinates a committee of strategic certifiers to sustain equilibrium among honest users and detec…
Game-theoretic Counterfactual Explanation for Graph Neural Networks
Chirag Chhablani, Sarthak Jain, Akshay Channesh +2
Graph Neural Networks (GNNs) have been a powerful tool for node classification tasks in complex networks. However, their decision-making processes remain a black-box to users, maki…
Keep-Alive Caching for the Hawkes process
Sushirdeep Narayana, Ian A. Kash
We study the design of caching policies in applications such as serverless computing where there is not a fixed size cache to be filled, but rather there is a cost associated with…
Slowly Changing Adversarial Bandit Algorithms are Efficient for Discounted MDPs
Ian A. Kash, Lev Reyzin, Zishun Yu
Reinforcement learning generalizes multi-armed bandit problems with additional difficulties of a longer planning horizon and unknown transition kernel. We explore a black-box reduc…
Fair Decision-Making for Food Inspections
Shubham Singh, Bhuvni Shah, Chris Kanich +1
Data and algorithms are essential and complementary parts of a large-scale decision-making process. However, their injudicious use can lead to unforeseen consequences, as has been…
Fairness Through Counterfactual Utilities
Jack Blandin, Ian Kash
Group fairness definitions such as Demographic Parity and Equal Opportunity make assumptions about the underlying decision-problem that restrict them to classification problems. Pr…