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Tung Mai
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2020 – today
- 2024
- [c28]Yu Xia, Xu Liu, Tong Yu, Sungchul Kim, Ryan A. Rossi, Anup B. Rao, Tung Mai, Shuai Li:
Hallucination Diversity-Aware Active Learning for Text Summarization. NAACL-HLT 2024: 8665-8677 - [i26]Yu Xia, Xu Liu, Tong Yu, Sungchul Kim, Ryan A. Rossi, Anup B. Rao, Tung Mai, Shuai Li:
Hallucination Diversity-Aware Active Learning for Text Summarization. CoRR abs/2404.01588 (2024) - 2023
- [c27]Tung Mai, Alexander Munteanu, Cameron Musco, Anup Rao, Chris Schwiegelshohn, David P. Woodruff:
Optimal Sketching Bounds for Sparse Linear Regression. AISTATS 2023: 11288-11316 - [c26]Gaurav Gupta, Anup B. Rao, Tung Mai, Ryan A. Rossi, Xiang Chen, Saayan Mitra, Anshumali Shrivastava:
Near Neighbor Search for Constraint Queries. IEEE Big Data 2023: 1707-1715 - [c25]Sudhanshu Chanpuriya, Ryan A. Rossi, Anup B. Rao, Tung Mai, Nedim Lipka, Zhao Song, Cameron Musco:
Exact Representation of Sparse Networks with Symmetric Nonnegative Embeddings. NeurIPS 2023 - [c24]Mehrdad Ghadiri, David Arbour, Tung Mai, Cameron Musco, Anup B. Rao:
Finite Population Regression Adjustment and Non-asymptotic Guarantees for Treatment Effect Estimation. NeurIPS 2023 - [c23]Aniket Murhekar, David Arbour, Tung Mai, Anup B. Rao:
Brief Announcement: Dynamic Vector Bin Packing for Online Resource Allocation in the Cloud. SPAA 2023: 307-310 - [i25]Tung Mai, Alexander Munteanu, Cameron Musco, Anup B. Rao, Chris Schwiegelshohn, David P. Woodruff:
Optimal Sketching Bounds for Sparse Linear Regression. CoRR abs/2304.02261 (2023) - [i24]Rohith Reddy Gangam, Tung Mai, Nitya Raju, Vijay V. Vazirani:
A Structural and Algorithmic Study of Stable Matching Lattices of Multiple Instances. CoRR abs/2304.02590 (2023) - [i23]Aniket Murhekar, David Arbour, Tung Mai, Anup Rao:
Dynamic Vector Bin Packing for Online Resource Allocation in the Cloud. CoRR abs/2304.08648 (2023) - 2022
- [c22]Nikhil Sheoran, Subrata Mitra, Vibhor Porwal, Siddharth Ghetia, Jatin Varshney, Tung Mai, Anup B. Rao, Vikas Maddukuri:
Conditional Generative Model Based Predicate-Aware Query Approximation. AAAI 2022: 8259-8266 - [c21]Rohith Reddy Gangam, Tung Mai, Nitya Raju, Vijay V. Vazirani:
A Structural and Algorithmic Study of Stable Matching Lattices of "Nearby" Instances, with Applications. FSTTCS 2022: 19:1-19:20 - [c20]David Arbour, Drew Dimmery, Tung Mai, Anup B. Rao:
Online Balanced Experimental Design. ICML 2022: 844-864 - [c19]Aravind Reddy, Ryan A. Rossi, Zhao Song, Anup B. Rao, Tung Mai, Nedim Lipka, Gang Wu, Eunyee Koh, Nesreen K. Ahmed:
One-Pass Algorithms for MAP Inference of Nonsymmetric Determinantal Point Processes. ICML 2022: 18463-18482 - [c18]Raghavendra Addanki, David Arbour, Tung Mai, Cameron Musco, Anup Rao:
Sample Constrained Treatment Effect Estimation. NeurIPS 2022 - [c17]Vibhor Porwal, Subrata Mitra, Fan Du, John Anderson, Nikhil Sheoran, Anup B. Rao, Tung Mai, Gautam Kowshik, Sapthotharan Nair, Sameeksha Arora, Saurabh Mahapatra:
Efficient Insights Discovery through Conditional Generative Model based Query Approximation. SIGMOD Conference 2022: 2397-2400 - [i22]Nikhil Sheoran, Subrata Mitra, Vibhor Porwal, Siddharth Ghetia, Jatin Varshney, Tung Mai, Anup B. Rao, Vikas Maddukuri:
Electra: Conditional Generative Model based Predicate-Aware Query Approximation. CoRR abs/2201.12420 (2022) - [i21]Raghavendra Addanki, David Arbour, Tung Mai, Cameron Musco, Anup Rao:
Sample Constrained Treatment Effect Estimation. CoRR abs/2210.06594 (2022) - 2021
- [c16]Jiong Zhu, Ryan A. Rossi, Anup Rao, Tung Mai, Nedim Lipka, Nesreen K. Ahmed, Danai Koutra:
Graph Neural Networks with Heterophily. AAAI 2021: 11168-11176 - [c15]Enayat Ullah, Tung Mai, Anup Rao, Ryan A. Rossi, Raman Arora:
Machine Unlearning via Algorithmic Stability. COLT 2021: 4126-4142 - [c14]Mohammad Mehrabi, Adel Javanmard, Ryan A. Rossi, Anup B. Rao, Tung Mai:
Fundamental Tradeoffs in Distributionally Adversarial Training. ICML 2021: 7544-7554 - [c13]Mojtaba Sahraee-Ardakan, Tung Mai, Anup B. Rao, Ryan A. Rossi, Sundeep Rangan, Alyson K. Fletcher:
Asymptotics of Ridge Regression in Convolutional Models. ICML 2021: 9265-9275 - [c12]Gromit Yeuk-Yin Chan, Tung Mai, Anup B. Rao, Ryan A. Rossi, Fan Du, Cláudio T. Silva, Juliana Freire:
Interactive Audience Expansion On Large Scale Online Visitor Data. KDD 2021: 2621-2631 - [c11]Tung Mai, Cameron Musco, Anup Rao:
Coresets for Classification - Simplified and Strengthened. NeurIPS 2021: 11643-11654 - [i20]Mohammad Mehrabi, Adel Javanmard, Ryan A. Rossi, Anup Rao, Tung Mai:
Fundamental Tradeoffs in Distributionally Adversarial Training. CoRR abs/2101.06309 (2021) - [i19]Enayat Ullah, Tung Mai, Anup Rao, Ryan A. Rossi, Raman Arora:
Machine Unlearning via Algorithmic Stability. CoRR abs/2102.13179 (2021) - [i18]Mojtaba Sahraee-Ardakan, Tung Mai, Anup B. Rao, Ryan A. Rossi, Sundeep Rangan, Alyson K. Fletcher:
Asymptotics of Ridge Regression in Convolutional Models. CoRR abs/2103.04557 (2021) - [i17]Tung Mai, Anup B. Rao, Cameron Musco:
Coresets for Classification - Simplified and Strengthened. CoRR abs/2106.04254 (2021) - [i16]Tung Mai, Anup B. Rao, Ryan A. Rossi, Saeed Seddighin:
Optimal Space and Time for Streaming Pattern Matching. CoRR abs/2107.04660 (2021) - [i15]Sudhanshu Chanpuriya, Ryan A. Rossi, Anup B. Rao, Tung Mai, Nedim Lipka, Zhao Song, Cameron Musco:
An Interpretable Graph Generative Model with Heterophily. CoRR abs/2111.03030 (2021) - [i14]Aravind Reddy, Ryan A. Rossi, Zhao Song, Anup B. Rao, Tung Mai, Nedim Lipka, Gang Wu, Eunyee Koh, Nesreen K. Ahmed:
Online MAP Inference and Learning for Nonsymmetric Determinantal Point Processes. CoRR abs/2111.14674 (2021) - 2020
- [c10]Karthik Gajulapalli, James A. Liu, Tung Mai, Vijay V. Vazirani:
Stability-Preserving, Time-Efficient Mechanisms for School Choice in Two Rounds. FSTTCS 2020: 21:1-21:15 - [c9]Alireza Farhadi, Mohammad Taghi Hajiaghayi, Tung Mai, Anup Rao, Ryan A. Rossi:
Approximate Maximum Matching in Random Streams. SODA 2020: 1773-1785 - [c8]Ryan A. Rossi, Anup Rao, Tung Mai, Nesreen K. Ahmed:
Fast and Accurate Estimation of Typed Graphlets. WWW (Companion Volume) 2020: 32-34 - [i13]Jiong Zhu, Ryan A. Rossi, Anup B. Rao, Tung Mai, Nedim Lipka, Nesreen K. Ahmed, Danai Koutra:
Graph Neural Networks with Heterophily. CoRR abs/2009.13566 (2020)
2010 – 2019
- 2019
- [c7]Tung Mai, Anup Rao, Matt Kapilevich, Ryan A. Rossi, Yasin Abbasi-Yadkori, Ritwik Sinha:
On Densification for Minwise Hashing. UAI 2019: 831-840 - [i12]Tung Mai, Vijay V. Vazirani:
Stability-Preserving, Incentive-Compatible, Time-Efficient Mechanisms for Increasing School Capacity. CoRR abs/1904.04431 (2019) - [i11]Alireza Farhadi, MohammadTaghi Hajiaghayi, Tung Mai, Anup Rao, Ryan A. Rossi:
Approximate Maximum Matching in Random Streams. CoRR abs/1912.10497 (2019) - 2018
- [c6]Tung Mai, Vijay V. Vazirani:
Finding Stable Matchings That Are Robust to Errors in the Input. ESA 2018: 60:1-60:11 - [c5]Tung Mai, Milena Mihail, Ioannis Panageas, Will Ratcliff, Vijay V. Vazirani, Peter Yunker:
Cycles in Zero-Sum Differential Games and Biological Diversity. EC 2018: 339-350 - [c4]Nima Anari, Tung Mai, Shayan Oveis Gharan, Vijay V. Vazirani:
Nash Social Welfare for Indivisible Items under Separable, Piecewise-Linear Concave Utilities. SODA 2018: 2274-2290 - [i10]Tung Mai, Vijay V. Vazirani:
A Natural Generalization of Stable Matching Solved via New Insights into Ideal Cuts. CoRR abs/1802.06621 (2018) - [i9]Tung Mai, Vijay V. Vazirani:
Finding Stable Matchings that are Robust to Errors in the Input. CoRR abs/1804.00553 (2018) - [i8]Tung Mai, Vijay V. Vazirani:
A Generalization of Birkhoff's Theorem for Distributive Lattices, with Applications to Robust Stable Matchings. CoRR abs/1804.05537 (2018) - 2017
- [c3]Tung Mai, Ioannis Panageas, Vijay V. Vazirani:
Opinion Dynamics in Networks: Convergence, Stability and Lack of Explosion. ICALP 2017: 140:1-140:14 - [c2]Richard Cole, Nikhil R. Devanur, Vasilis Gkatzelis, Kamal Jain, Tung Mai, Vijay V. Vazirani, Sadra Yazdanbod:
Convex Program Duality, Fisher Markets, and Nash Social Welfare. EC 2017: 459-460 - [c1]Kamal Jain, Tung Mai, Vijay V. Vazirani:
A Performance-Based Scheme for Pricing Resources in the Cloud. WINE 2017: 281-293 - [i7]Tung Mai, Richard Peng, Anup B. Rao, Vijay V. Vazirani:
Concave Flow on Small Depth Directed Networks. CoRR abs/1704.07791 (2017) - [i6]Tung Mai, Ioannis Panageas, Will Ratcliff, Vijay V. Vazirani, Peter Yunker:
Rock-Paper-Scissors, Differential Games and Biological Diversity. CoRR abs/1710.11249 (2017) - 2016
- [i5]Nikhil R. Devanur, Kamal Jain, Tung Mai, Vijay V. Vazirani, Sadra Yazdanbod:
New Convex Programs for Fisher's Market Model and its Generalizations. CoRR abs/1603.01257 (2016) - [i4]Tung Mai, Ioannis Panageas, Vijay V. Vazirani:
Opinion Dynamics in Networks: Convergence, Stability and Lack of Explosion. CoRR abs/1607.03881 (2016) - [i3]Richard Cole, Nikhil R. Devanur, Vasilis Gkatzelis, Kamal Jain, Tung Mai, Vijay V. Vazirani, Sadra Yazdanbod:
Convex Program Duality, Fisher Markets, and Nash Social Welfare. CoRR abs/1609.06654 (2016) - [i2]Kamal Jain, Tung Mai, Vijay V. Vazirani:
A Performance-Based Scheme for Pricing Resources in the Cloud. CoRR abs/1610.00157 (2016) - [i1]Nima Anari, Tung Mai, Shayan Oveis Gharan, Vijay V. Vazirani:
Nash Social Welfare for Indivisible Items under Separable, Piecewise-Linear Concave Utilities. CoRR abs/1612.05191 (2016)
Coauthor Index
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last updated on 2024-09-02 01:01 CEST by the dblp team
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