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ORCIDUthaipon Tao Tantipongpipat
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2020 – today
- 2023
[j6]Tomo Lazovich, Luca Belli, Aaron Gonzales, Amanda Bower, Uthaipon Tantipongpipat, Kristian Lum, Ferenc Huszár, Rumman Chowdhury:
Measuring disparate outcomes of content recommendation algorithms with distributional inequality metrics. Patterns 4(8): 100822 (2023)- 2022
- [j5]Aleksandar Nikolov, Mohit Singh, Uthaipon Tao Tantipongpipat
:
Proportional Volume Sampling and Approximation Algorithms for A-Optimal Design. Math. Oper. Res. 47(2): 847-877 (2022) - [j4]Tomo Lazovich, Luca Belli, Aaron Gonzales, Amanda Bower, Uthaipon Tantipongpipat, Kristian Lum, Ferenc Huszár, Rumman Chowdhury:
Measuring disparate outcomes of content recommendation algorithms with distributional inequality metrics. Patterns 3(8): 100568 (2022) - [i11]Tomo Lazovich, Luca Belli, Aaron Gonzales, Amanda Bower, Uthaipon Tantipongpipat, Kristian Lum, Ferenc Huszar, Rumman Chowdhury:
Measuring Disparate Outcomes of Content Recommendation Algorithms with Distributional Inequality Metrics. CoRR abs/2202.01615 (2022) - [i10]Luca Belli, Kyra Yee, Uthaipon Tantipongpipat, Aaron Gonzales, Kristian Lum, Moritz Hardt:
County-level Algorithmic Audit of Racial Bias in Twitter's Home Timeline. CoRR abs/2211.08667 (2022) - 2021
- [j3]Uthaipon Tao Tantipongpipat, Chris Waites, Digvijay Boob, Amaresh Ankit Siva, Rachel Cummings:
Differentially private synthetic mixed-type data generation for unsupervised learning. Intell. Decis. Technol. 15(4): 779-807 (2021) - [j2]Kyra Yee, Uthaipon Tantipongpipat, Shubhanshu Mishra:
Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency. Proc. ACM Hum. Comput. Interact. 5(CSCW2): 450:1-450:24 (2021) - [c8]Uthaipon Tao Tantipongpipat, Chris Waites, Digvijay Boob, Amaresh Ankit Siva, Rachel Cummings:
Differentially Private Synthetic Mixed-Type Data Generation For Unsupervised Learning. IISA 2021: 1-9 - [c7]Zhiqi Bu, Sivakanth Gopi, Janardhan Kulkarni, Yin Tat Lee, Judy Hanwen Shen, Uthaipon Tantipongpipat:
Fast and Memory Efficient Differentially Private-SGD via JL Projections. NeurIPS 2021: 19680-19691 - [i9]Zhiqi Bu, Sivakanth Gopi, Janardhan Kulkarni, Yin Tat Lee, Judy Hanwen Shen, Uthaipon Tantipongpipat:
Fast and Memory Efficient Differentially Private-SGD via JL Projections. CoRR abs/2102.03013 (2021) - [i8]Kyra Yee, Uthaipon Tantipongpipat, Shubhanshu Mishra:
Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency. CoRR abs/2105.08667 (2021) - 2020
- [b1]Uthaipon Tantipongpipat:
Fair and Diverse Data Representation in Machine Learning. Georgia Institute of Technology, Atlanta, GA, USA, 2020 - [c6]Vivek Madan, Aleksandar Nikolov, Mohit Singh, Uthaipon Tantipongpipat:
Maximizing Determinants under Matroid Constraints. FOCS 2020: 565-576 - [i7]Vivek Madan, Aleksandar Nikolov, Mohit Singh, Uthaipon Tantipongpipat:
Maximizing Determinants under Matroid Constraints. CoRR abs/2004.07886 (2020) - [i6]Uthaipon Tantipongpipat:
λ-Regularized A-Optimal Design and its Approximation by λ-Regularized Proportional Volume Sampling. CoRR abs/2006.11182 (2020)
2010 – 2019
- 2019
- [c5]Vivek Madan, Mohit Singh, Uthaipon Tantipongpipat, Weijun Xie:
Combinatorial Algorithms for Optimal Design. COLT 2019: 2210-2258 - [c4]Uthaipon Tantipongpipat, Samira Samadi, Mohit Singh, Jamie Morgenstern, Santosh S. Vempala:
Multi-Criteria Dimensionality Reduction with Applications to Fairness. NeurIPS 2019: 15135-15145 - [c3]Aleksandar Nikolov, Mohit Singh, Uthaipon Tao Tantipongpipat:
Proportional Volume Sampling and Approximation Algorithms for A-Optimal Design. SODA 2019: 1369-1386 - [i5]Jamie Morgenstern, Samira Samadi, Mohit Singh, Uthaipon Tao Tantipongpipat, Santosh S. Vempala:
Fair Dimensionality Reduction and Iterative Rounding for SDPs. CoRR abs/1902.11281 (2019) - [i4]Uthaipon Tantipongpipat, Chris Waites, Digvijay Boob, Amaresh Ankit Siva, Rachel Cummings:
Differentially Private Mixed-Type Data Generation For Unsupervised Learning. CoRR abs/1912.03250 (2019) - 2018
- [c2]Rachel Cummings, Sara Krehbiel, Kevin A. Lai, Uthaipon Tao Tantipongpipat:
Differential Privacy for Growing Databases. NeurIPS 2018: 8878-8887 - [c1]Samira Samadi, Uthaipon Tao Tantipongpipat, Jamie Morgenstern, Mohit Singh, Santosh S. Vempala:
The Price of Fair PCA: One Extra dimension. NeurIPS 2018: 10999-11010 - [i3]Aleksandar Nikolov, Mohit Singh, Uthaipon Tao Tantipongpipat:
Proportional Volume Sampling and Approximation Algorithms for A-Optimal Design. CoRR abs/1802.08318 (2018) - [i2]Rachel Cummings, Sara Krehbiel, Kevin A. Lai, Uthaipon Tantipongpipat:
Differential Privacy for Growing Databases. CoRR abs/1803.06416 (2018) - [i1]Samira Samadi, Uthaipon Tao Tantipongpipat, Jamie Morgenstern, Mohit Singh, Santosh S. Vempala:
The Price of Fair PCA: One Extra Dimension. CoRR abs/1811.00103 (2018) - 2014
- [j1]Uthaipon Tantipongpipat:
A Combinatorial Approach to Ebert's Hat Game with Many Colors. Electron. J. Comb. 21(4): 4 (2014)
Coauthor Index
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