most citedModel Explanations with Differential Privacy

3 citations · 3 across the 2 of their papers we have counts for

collaborators

7 papers

cs.DS2022

On Sparsification of Stochastic Packing Problems

Shaddin Dughmi, Yusuf Hakan Kalayci, Neel Patel

Motivated by recent progress on stochastic matching with few queries, we embark on a systematic study of the sparsification of stochastic packing problems (SPP) more generally. Spe…

cs.GT2022

Delegated Pandora's box

Curtis Bechtel, Shaddin Dughmi, Neel Patel

In delegation problems, a principal does not have the resources necessary to complete a particular task, so they delegate the task to an untrusted agent whose interests may differ…

cs.GT2020

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…

cs.LG20203 cited

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…

cs.LG2020

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…

cs.GT2020

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…