154 citations · 639 across the 138 of their papers we have counts for
11 papers · 1 filter
Incentivizing Truthfulness Through Audits in Strategic Classification
Andrew Estornell, Sanmay Das, Yevgeniy Vorobeychik
In many societal resource allocation domains, machine learning methods are increasingly used to either score or rank agents in order to decide which ones should receive either reso…
Blocking Adversarial Influence in Social Networks
Feiran Jia, Kai Zhou, Charles Kamhoua +1
While social networks are widely used as a media for information diffusion, attackers can also strategically employ analytical tools, such as influence maximization, to maximize th…
Finding Physical Adversarial Examples for Autonomous Driving with Fast and Differentiable Image Compositing
Jinghan Yang, Adith Boloor, Ayan Chakrabarti +2
There is considerable evidence that deep neural networks are vulnerable to adversarial perturbations applied directly to their digital inputs. However, it remains an open question…
Optimizing Graph Structure for Targeted Diffusion
Sixie Yu, Leonardo Torres, Scott Alfeld +2
The problem of diffusion control on networks has been extensively studied, with applications ranging from marketing to controlling infectious disease. However, in many applications…
Robust Collective Classification against Structural Attacks
Kai Zhou, Yevgeniy Vorobeychik
Collective learning methods exploit relations among data points to enhance classification performance. However, such relations, represented as edges in the underlying graphical mod…
Election Control by Manipulating Issue Significance
Andrew Estornell, Sanmay Das, Edith Elkind +1
Integrity of elections is vital to democratic systems, but it is frequently threatened by malicious actors. The study of algorithmic complexity of the problem of manipulating elect…