203 citations · 288 across the 21 of their papers we have counts for
6 papers · 1 filter
Optimizing Group-Fair Plackett-Luce Ranking Models for Relevance and Ex-Post Fairness
Sruthi Gorantla, Eshaan Bhansali, Amit Deshpande +1
In learning-to-rank (LTR), optimizing only the relevance (or the expected ranking utility) can cause representational harm to certain categories of items. Moreover, if there is imp…
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…
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…
Robust Identifiability in Linear Structural Equation Models of Causal Inference
Karthik Abinav Sankararaman, Anand Louis, Navin Goyal
In this work, we consider the problem of robust parameter estimation from observational data in the context of linear structural equation models (LSEMs). LSEMs are a popular and we…
Stability of Linear Structural Equation Models of Causal Inference
Karthik Abinav Sankararaman, Anand Louis, Navin Goyal
We consider the numerical stability of the parameter recovery problem in Linear Structural Equation Model ($\LSEM$) of causal inference. A long line of work starting from Wright (1…
HyperGCN: A New Method of Training Graph Convolutional Networks on Hypergraphs
Naganand Yadati, Madhav Nimishakavi, Prateek Yadav +3
In many real-world network datasets such as co-authorship, co-citation, email communication, etc., relationships are complex and go beyond pairwise. Hypergraphs provide a flexible…