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20162023
most citedOnline Algorithms for Matchings with Proportional Fairness Constraints and Diversity Constraints

3 citations · 4 across the 8 of their papers we have counts for

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Showing 2022Show all

6 papers · 1 filter

cs.LG2022★ 1 cited

Socially Fair Center-based and Linear Subspace Clustering

Sruthi Gorantla, Kishen N. Gowda, Amit Deshpande +1

Center-based clustering (e.g., -means, -medians) and clustering using linear subspaces are two most popular techniques to partition real-world data into smaller clusters. How…

cs.DS2022★ 3 cited

Online Algorithms for Matchings with Proportional Fairness Constraints and Diversity Constraints

Anand Louis, Meghana Nasre, Prajakta Nimbhorkar +1

Matching problems with group-fairness constraints and diversity constraints have numerous applications such as in allocation problems, committee selection, school choice, etc. More…

cs.AI2022

Individual Fairness under Varied Notions of Group Fairness in Bipartite Matching - One Framework to Approximate Them All

Atasi Panda, Anand Louis, Prajakta Nimbhorkar

We study the probabilistic assignment of items to platforms that satisfies both group and individual fairness constraints. Each item belongs to specific groups and has a preference…

cs.DS2022

Approximating CSPs with Outliers

Suprovat Ghoshal, Anand Louis

Constraint satisfaction problems (CSPs) are ubiquitous in theoretical computer science. We study the problem of StrongCSPs, i.e. instances where a large induced sub-instance has a…

cs.DS2022

Exact recovery algorithm for Planted Bipartite Graph in Semi-random Graphs

Akash Kumar, Anand Louis, Rameesh Paul

The problem of finding the largest induced balanced bipartite subgraph in a given graph is NP-hard. This problem is closely related to the problem of finding the smallest Odd Cycle…

cs.LG2022

Sampling Ex-Post Group-Fair Rankings

Sruthi Gorantla, Amit Deshpande, Anand Louis

Randomized rankings have been of recent interest to achieve ex-ante fairer exposure and better robustness than deterministic rankings. We propose a set of natural axioms for random…