60 citations · 65 across the 7 of their papers we have counts for
7 papers
Uncertainty Quantification for Local Model Explanations Without Model Access
Surin Ahn, Justin Grana, Yafet Tamene +1
We present a model-agnostic algorithm for generating post-hoc explanations and uncertainty intervals for a machine learning model when only a static sample of inputs and outputs fr…
Content Filtering with Inattentive Information Consumers
Ian Ball, James Bono, Justin Grana +3
We develop a model of content filtering as a game between the filter and the content consumer, where the latter incurs information costs for examining the content. Motivating examp…
Policy-focused Agent-based Modeling using RL Behavioral Models
Osonde A. Osoba, Raffaele Vardavas, Justin Grana +2
Agent-based Models (ABMs) are valuable tools for policy analysis. ABMs help analysts explore the emergent consequences of policy interventions in multi-agent decision-making settin…
Perturbing Inputs to Prevent Model Stealing
Justin Grana
We show how perturbing inputs to machine learning services (ML-service) deployed in the cloud can protect against model stealing attacks. In our formulation, there is an ML-service…
Deep Reinforcement Learning for Event-Driven Multi-Agent Decision Processes
Kunal Menda, Yi-Chun Chen, Justin Grana +4
The incorporation of macro-actions (temporally extended actions) into multi-agent decision problems has the potential to address the curse of dimensionality associated with such de…
Modeling Social Organizations as Communication Networks
David Wolpert, Justin Grana, Brendan Tracey +2
We identify the "organization" of a human social group as the communication network(s) within that group. We then introduce three theoretical approaches to analyzing what determine…
A Likelihood Ratio Detector for Identifying Within-Perimeter Computer Network Attacks
Justin Grana, David Wolpert, Joshua Neil +3
The rapid detection of attackers within firewalls of enterprise computer net- works is of paramount importance. Anomaly detectors address this problem by quantifying deviations fro…