11 citations · 34 across the 10 of their papers we have counts for
10 papers
Adversarial Machine Unlearning
Zonglin Di, Sixie Yu, Yevgeniy Vorobeychik +1
This paper focuses on the challenge of machine unlearning, aiming to remove the influence of specific training data on machine learning models. Traditionally, the development of un…
Altruism Design in Networked Public Goods Games
Sixie Yu, David Kempe, Yevgeniy Vorobeychik
Many collective decision-making settings feature a strategic tension between agents acting out of individual self-interest and promoting a common good. These include wearing face m…
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…
Inducing Equilibria in Networked Public Goods Games through Network Structure Modification
David Kempe, Sixie Yu, Yevgeniy Vorobeychik
Networked public goods games model scenarios in which self-interested agents decide whether or how much to invest in an action that benefits not only themselves, but also their net…
Computing Equilibria in Binary Networked Public Goods Games
Sixie Yu, Kai Zhou, P. Jeffrey Brantingham +1
Public goods games study the incentives of individuals to contribute to a public good and their behaviors in equilibria. In this paper, we examine a specific type of public goods g…
Distributionally Robust Removal of Malicious Nodes from Networks
Sixie Yu, Yevgeniy Vorobeychik
An important problem in networked systems is detection and removal of suspected malicious nodes. A crucial consideration in such settings is the uncertainty endemic in detection, c…
Removing Malicious Nodes from Networks
Sixie Yu, Yevgeniy Vorobeychik
A fundamental challenge in networked systems is detection and removal of suspected malicious nodes. In reality, detection is always imperfect, and the decision about which potentia…
Adversarial Coordination on Social Networks
Chen Hajaj, Sixie Yu, Zlatko Joveski +1
Decentralized coordination is one of the fundamental challenges for societies and organizations. While extensively explored from a variety of perspectives, one issue which has rece…
Adversarial Regression with Multiple Learners
Liang Tong, Sixie Yu, Scott Alfeld +1
Despite the considerable success enjoyed by machine learning techniques in practice, numerous studies demonstrated that many approaches are vulnerable to attacks. An important clas…
Adversarial Classification on Social Networks
Sixie Yu, Yevgeniy Vorobeychik, Scott Alfeld
The spread of unwanted or malicious content through social media has become a major challenge. Traditional examples of this include social network spam, but an important new concer…