17 citations · 20 across the 2 of their papers we have counts for
8 papers
The Price is (Probably) Right: Learning Market Equilibria from Samples
Vignesh Viswanathan, Omer Lev, Neel Patel +1
Equilibrium computation in markets usually considers settings where player valuation functions are known. We consider the setting where player valuations are unknown; using a PAC l…
Model Explanations with Differential Privacy
Neel Patel, Reza Shokri, Yair Zick
Black-box machine learning models are used in critical decision-making domains, giving rise to several calls for more algorithmic transparency. The drawback is that model explanati…
High Dimensional Model Explanations: an Axiomatic Approach
Neel Patel, Martin Strobel, Yair Zick
Complex black-box machine learning models are regularly used in critical decision-making domains. This has given rise to several calls for algorithmic explainability. Many explanat…
Keeping Your Friends Close: Land Allocation with Friends
Edith Elkind, Neel Patel, Alan Tsang +1
We examine the problem of assigning plots of land to prospective buyers who prefer living next to their friends. They care not only about the plot they receive, but also about thei…
On the Privacy Risks of Model Explanations
Reza Shokri, Martin Strobel, Yair Zick
Privacy and transparency are two key foundations of trustworthy machine learning. Model explanations offer insights into a model's decisions on input data, whereas privacy is prima…
Group-Fairness in Influence Maximization
Alan Tsang, Bryan Wilder, Eric Rice +2
Influence maximization is a widely used model for information dissemination in social networks. Recent work has employed such interventions across a wide range of social problems,…