1 citations · 3 across the 8 of their papers we have counts for
8 papers
On Socially Fair Low-Rank Approximation and Column Subset Selection
Zhao Song, Ali Vakilian, David P. Woodruff +1
Low-rank approximation and column subset selection are two fundamental and related problems that are applied across a wealth of machine learning applications. In this paper, we stu…
Learning-Based Algorithms for Graph Searching Problems
Adela Frances DePavia, Erasmo Tani, Ali Vakilian
We consider the problem of graph searching with prediction recently introduced by Banerjee et al. (2022). In this problem, an agent, starting at some vertex has to traverse a (…
Scalable Algorithms for Individual Preference Stable Clustering
Ron Mosenzon, Ali Vakilian
In this paper, we study the individual preference (IP) stability, which is an notion capturing individual fairness and stability in clustering. Within this setting, a clustering is…
Bayesian Strategic Classification
Lee Cohen, Saeed Sharifi-Malvajerdi, Kevin Stangl +2
In strategic classification, agents modify their features, at a cost, to ideally obtain a positive classification from the learner's classifier. The typical response of the learner…
Tight Bounds for Volumetric Spanners and Applications
Aditya Bhaskara, Sepideh Mahabadi, Ali Vakilian
Given a set of points of interest, a volumetric spanner is a subset of the points using which all the points can be expressed using "small" coefficients (measured in an appropriate…
Constant Approximation for Individual Preference Stable Clustering
Anders Aamand, Justin Y. Chen, Allen Liu +4
Individual preference (IP) stability, introduced by Ahmadi et al. (ICML 2022), is a natural clustering objective inspired by stability and fairness constraints. A clustering is …