77 citations · 194 across the 10 of their papers we have counts for
11 papers
County-level Algorithmic Audit of Racial Bias in Twitter's Home Timeline
Luca Belli, Kyra Yee, Uthaipon Tantipongpipat +3
We report on the outcome of an audit of Twitter's Home Timeline ranking system. The goal of the audit was to determine if authors from some racial groups experience systematically…
Measuring Disparate Outcomes of Content Recommendation Algorithms with Distributional Inequality Metrics
Tomo Lazovich, Luca Belli, Aaron Gonzales +5
The harmful impacts of algorithmic decision systems have recently come into focus, with many examples of systems such as machine learning (ML) models amplifying existing societal b…
Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency
Kyra Yee, Uthaipon Tantipongpipat, Shubhanshu Mishra
Twitter uses machine learning to crop images, where crops are centered around the part predicted to be the most salient. In fall 2020, Twitter users raised concerns that the automa…
Fast and Memory Efficient Differentially Private-SGD via JL Projections
Zhiqi Bu, Sivakanth Gopi, Janardhan Kulkarni +3
Differentially Private-SGD (DP-SGD) of Abadi et al. (2016) and its variations are the only known algorithms for private training of large scale neural networks. This algorithm requ…
-Regularized A-Optimal Design and its Approximation by -Regularized Proportional Volume Sampling
Uthaipon Tantipongpipat
In this work, we study the -regularized -optimal design problem and introduce the -regularized proportional volume sampling algorithm, generalized from [Nikolov, Singh, an…
Maximizing Determinants under Matroid Constraints
Vivek Madan, Aleksandar Nikolov, Mohit Singh +1
Given vectors and a matroid , we study the problem of finding a basis of such that is maximized…
Differentially Private Synthetic Mixed-Type Data Generation For Unsupervised Learning
Uthaipon Tantipongpipat, Chris Waites, Digvijay Boob +2
We introduce the DP-auto-GAN framework for synthetic data generation, which combines the low dimensional representation of autoencoders with the flexibility of Generative Adversari…
Multi-Criteria Dimensionality Reduction with Applications to Fairness
Uthaipon Tantipongpipat, Samira Samadi, Mohit Singh +2
Dimensionality reduction is a classical technique widely used for data analysis. One foundational instantiation is Principal Component Analysis (PCA), which minimizes the average r…
The Price of Fair PCA: One Extra Dimension
Samira Samadi, Uthaipon Tantipongpipat, Jamie Morgenstern +2
We investigate whether the standard dimensionality reduction technique of PCA inadvertently produces data representations with different fidelity for two different populations. We…
Differential Privacy for Growing Databases
Rachel Cummings, Sara Krehbiel, Kevin A. Lai +1
We study the design of differentially private algorithms for adaptive analysis of dynamically growing databases, where a database accumulates new data entries while the analysis is…
Proportional Volume Sampling and Approximation Algorithms for A-Optimal Design
Aleksandar Nikolov, Mohit Singh, Uthaipon Tao Tantipongpipat
We study the optimal design problems where the goal is to choose a set of linear measurements to obtain the most accurate estimate of an unknown vector in dimensions. We study…