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02/05/2023
Improving Fair Training under Correlation Shifts
Model fairness is an essential element for Trustworthy AI. While many te...
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10/12/2022
Equal Experience in Recommender Systems
We explore the fairness issue that arises in recommender systems. Biased...
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01/02/2022
Matrix Completion with Hierarchical Graph Side Information
We consider a matrix completion problem that exploits social or item sim...
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10/27/2021
Sample Selection for Fair and Robust Training
Fairness and robustness are critical elements of Trustworthy AI that nee...
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09/12/2021
On the Fundamental Limits of Matrix Completion: Leveraging Hierarchical Similarity Graphs
We study the matrix completion problem that leverages hierarchical simil...
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12/03/2020
FairBatch: Batch Selection for Model Fairness
Training a fair machine learning model is essential to prevent demograph...
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06/08/2020
MC2G: An Efficient Algorithm for Matrix Completion with Social and Item Similarity Graphs
We consider a discrete-valued matrix completion problem for recommender ...
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02/24/2020
FR-Train: A mutual information-based approach to fair and robust training
Trustworthy AI is a critical issue in machine learning where, in additio...
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12/06/2019
Community Detection and Matrix Completion with Two-Sided Graph Side-Information
We consider the problem of recovering communities of users and communiti...
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02/25/2019
Wasserstein GAN Can Perform PCA
Generative Adversarial Networks (GANs) have become a powerful framework ...
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10/23/2018
Two-way Function Computation
We explore the role of interaction for the problem of reliable computati...
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05/23/2018
Hypergraph Spectral Clustering in the Weighted Stochastic Block Model
Spectral clustering is a celebrated algorithm that partitions objects ba...
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01/15/2018
Hierarchical Coding for Distributed Computing
Coding for distributed computing supports low-latency computation by rel...
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10/30/2017
Understanding GANs: the LQG Setting
Generative Adversarial Networks (GANs) have become a popular method to l...
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09/12/2017
Community Recovery in Hypergraphs
Community recovery is a central problem that arises in a wide variety of...
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03/14/2016
Top-K Ranking from Pairwise Comparisons: When Spectral Ranking is Optimal
We explore the top-K rank aggregation problem. Suppose a collection of i...
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02/15/2016
Adversarial Top-K Ranking
We study the top-K ranking problem where the goal is to recover the set ...
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04/27/2015
Spectral MLE: Top-K Rank Aggregation from Pairwise Comparisons
This paper explores the preference-based top-K rank aggregation problem....
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04/06/2015