85 citations · 130 across the 9 of their papers we have counts for
10 papers
Classification with Partially Private Features
Zeyu Shen, Anilesh Krishnaswamy, Janardhan Kulkarni +1
In this paper, we consider differentially private classification when some features are sensitive, while the rest of the features and the label are not. We adapt the definition of…
Classification with Strategically Withheld Data
Anilesh K. Krishnaswamy, Haoming Li, David Rein +2
Machine learning techniques can be useful in applications such as credit approval and college admission. However, to be classified more favorably in such contexts, an agent may dec…
Fair for All: Best-effort Fairness Guarantees for Classification
Anilesh K. Krishnaswamy, Zhihao Jiang, Kangning Wang +2
Standard approaches to group-based notions of fairness, such as \emph{parity} and \emph{equalized odds}, try to equalize absolute measures of performance across known groups (based…
Knapsack Voting for Participatory Budgeting
Ashish Goel, Anilesh K. Krishnaswamy, Sukolsak Sakshuwong +1
We address the question of aggregating the preferences of voters in the context of participatory budgeting. We scrutinize the voting method currently used in practice, underline it…
Assortment planning for two-sided sequential matching markets
Itai Ashlagi, Anilesh K. Krishnaswamy, Rahul Makhijani +2
Two-sided matching platforms provide users with menus of match recommendations. To maximize the number of realized matches between the two sides (referred here as customers and sup…
Exploration vs. Exploitation in Team Formation
Ramesh Johari, Vijay Kamble, Anilesh K. Krishnaswamy +1
An online labor platform faces an online learning problem in matching workers with jobs and using the performance on these jobs to create better future matches. This learning probl…
Relating Metric Distortion and Fairness of Social Choice Rules
Ashish Goel, Reyna Hulett, Anilesh K. Krishnaswamy
One way of evaluating social choice (voting) rules is through a utilitarian distortion framework. In this model, we assume that agents submit full rankings over the alternatives, a…
Implementing the Lexicographic Maxmin Bargaining Solution
Ashish Goel, Anilesh K. Krishnaswamy
There has been much work on exhibiting mechanisms that implement various bargaining solutions, in particular, the Kalai-Smorodinsky solution \cite{moulin1984implementing} and the N…
Re-incentivizing Discovery: Mechanisms for Partial-Progress Sharing in Research
Anilesh Kollagunta Krishnaswamy, Ashish Goel, Siddhartha Banerjee
An essential primitive for an efficient research ecosystem is \emph{partial-progress sharing} (PPS) -- whereby a researcher shares information immediately upon making a breakthroug…
Metric Distortion of Social Choice Rules: Lower Bounds and Fairness Properties
Ashish Goel, Anilesh Kollagunta Krishnaswamy, Kamesh Munagala
We study social choice rules under the utilitarian distortion framework, with an additional metric assumption on the agents' costs over the alternatives. In this approach, these co…