New Convex Programs for Fisher's Market Model and its Generalizations. - Nikhil R. Devanur; Kamal Jain; Tung Mai; Vijay V. Vazirani; Sadra Yazdanbod (CoRR, 2016)

Opinion Dynamics in Networks: Convergence, Stability and Lack of Explosion. - Tung Mai; Ioannis Panageas; Vijay V. Vazirani (ICALP, 2017)

Convex Program Duality, Fisher Markets, and Nash Social Welfare. - Richard Cole 001; Nikhil R. Devanur; Vasilis Gkatzelis; Kamal Jain; Tung Mai; Vijay V. Vazirani; Sadra Yazdanbod (EC, 2017)

A Performance-Based Scheme for Pricing Resources in the Cloud. - Kamal Jain; Tung Mai; Vijay V. Vazirani (WINE, 2017)

Concave Flow on Small Depth Directed Networks. - Tung Mai; Richard Peng; Anup B. Rao; Vijay V. Vazirani (CoRR, 2017)

Rock-Paper-Scissors, Differential Games and Biological Diversity. - Tung Mai; Ioannis Panageas; Will Ratcliff; Vijay V. Vazirani; Peter Yunker (CoRR, 2017)

Finding Stable Matchings That Are Robust to Errors in the Input. - Tung Mai; Vijay V. Vazirani (ESA, 2018)

Cycles in Zero-Sum Differential Games and Biological Diversity. - Tung Mai; Milena Mihail; Ioannis Panageas; Will Ratcliff; Vijay V. Vazirani; Peter Yunker (EC, 2018)

Nash Social Welfare for Indivisible Items under Separable, Piecewise-Linear Concave Utilities. - Nima Anari; Tung Mai; Shayan Oveis Gharan; Vijay V. Vazirani (SODA, 2018)

A Natural Generalization of Stable Matching Solved via New Insights into Ideal Cuts. - Tung Mai; Vijay V. Vazirani (CoRR, 2018)

A Generalization of Birkhoff's Theorem for Distributive Lattices, with Applications to Robust Stable Matchings. - Tung Mai; Vijay V. Vazirani (CoRR, 2018)

On Densification for Minwise Hashing. - Tung Mai; Anup Rao 002; Matt Kapilevich; Ryan A. Rossi; Yasin Abbasi-Yadkori; Ritwik Sinha (UAI, 2019)

Stability-Preserving, Incentive-Compatible, Time-Efficient Mechanisms for Increasing School Capacity. - Tung Mai; Vijay V. Vazirani (CoRR, 2019)

Stability-Preserving, Time-Efficient Mechanisms for School Choice in Two Rounds. - Karthik Gajulapalli; James A. Liu; Tung Mai; Vijay V. Vazirani (FSTTCS, 2020)

Approximate Maximum Matching in Random Streams. - Alireza Farhadi 001; Mohammad Taghi Hajiaghayi; Tung Mai; Anup Rao 002; Ryan A. Rossi (SODA, 2020)

Fast and Accurate Estimation of Typed Graphlets. - Ryan A. Rossi; Anup Rao 002; Tung Mai; Nesreen K. Ahmed (WWW (Companion Volume), 2020)

Graph Neural Networks with Heterophily. - Jiong Zhu; Ryan A. Rossi; Anup Rao 002; Tung Mai; Nedim Lipka; Nesreen K. Ahmed; Danai Koutra (AAAI, 2021)

Machine Unlearning via Algorithmic Stability. - Enayat Ullah; Tung Mai; Anup Rao 002; Ryan A. Rossi; Raman Arora (COLT, 2021)

Fundamental Tradeoffs in Distributionally Adversarial Training. - Mohammad Mehrabi; Adel Javanmard; Ryan A. Rossi; Anup B. Rao; Tung Mai (ICML, 2021)

Asymptotics of Ridge Regression in Convolutional Models. - Mojtaba Sahraee-Ardakan; Tung Mai; Anup B. Rao; Ryan A. Rossi; Sundeep Rangan; Alyson K. Fletcher (ICML, 2021)

Interactive Audience Expansion On Large Scale Online Visitor Data. - Gromit Yeuk-Yin Chan; Tung Mai; Anup B. Rao; Ryan A. Rossi; Fan Du; Cláudio T. Silva; Juliana Freire (KDD, 2021)

Coresets for Classification - Simplified and Strengthened. - Tung Mai; Cameron Musco; Anup Rao 002 (NeurIPS, 2021)

Optimal Space and Time for Streaming Pattern Matching. - Tung Mai; Anup B. Rao; Ryan A. Rossi; Saeed Seddighin (CoRR, 2021)

An Interpretable Graph Generative Model with Heterophily. - Sudhanshu Chanpuriya; Ryan A. Rossi; Anup B. Rao; Tung Mai; Nedim Lipka; Zhao Song 002; Cameron Musco (CoRR, 2021)

Online MAP Inference and Learning for Nonsymmetric Determinantal Point Processes. - Aravind Reddy; Ryan A. Rossi; Zhao Song 002; Anup B. Rao; Tung Mai; Nedim Lipka; Gang Wu 013; Eunyee Koh; Nesreen K. Ahmed (CoRR, 2021)

Conditional Generative Model Based Predicate-Aware Query Approximation. - Nikhil Sheoran; Subrata Mitra; Vibhor Porwal; Siddharth Ghetia; Jatin Varshney; Tung Mai; Anup B. Rao; Vikas Maddukuri (AAAI, 2022)

A Structural and Algorithmic Study of Stable Matching Lattices of "Nearby" Instances, with Applications. - Rohith Reddy Gangam; Tung Mai; Nitya Raju; Vijay V. Vazirani (FSTTCS, 2022)

Online Balanced Experimental Design. - David Arbour; Drew Dimmery; Tung Mai; Anup B. Rao (ICML, 2022)

One-Pass Algorithms for MAP Inference of Nonsymmetric Determinantal Point Processes. - Aravind Reddy; Ryan A. Rossi; Zhao Song 002; Anup B. Rao; Tung Mai; Nedim Lipka; Gang Wu 013; Eunyee Koh; Nesreen K. Ahmed (ICML, 2022)

Sample Constrained Treatment Effect Estimation. - Raghavendra Addanki; David Arbour; Tung Mai; Cameron Musco; Anup Rao 002 (NeurIPS, 2022)

Efficient Insights Discovery through Conditional Generative Model based Query Approximation. - Vibhor Porwal; Subrata Mitra; Fan Du; John Anderson; Nikhil Sheoran; Anup B. Rao; Tung Mai; Gautam Kowshik; Sapthotharan Nair; Sameeksha Arora; Saurabh Mahapatra (SIGMOD Conference, 2022)

Electra: Conditional Generative Model based Predicate-Aware Query Approximation. - Nikhil Sheoran; Subrata Mitra; Vibhor Porwal; Siddharth Ghetia; Jatin Varshney; Tung Mai; Anup B. Rao; Vikas Maddukuri (CoRR, 2022)

Optimal Sketching Bounds for Sparse Linear Regression. - Tung Mai; Alexander Munteanu; Cameron Musco; Anup Rao 002; Chris Schwiegelshohn; David P. Woodruff (AISTATS, 2023)

Near Neighbor Search for Constraint Queries. - Gaurav Gupta; Anup B. Rao; Tung Mai; Ryan A. Rossi; Xiang Chen; Saayan Mitra; Anshumali Shrivastava (IEEE Big Data, 2023)

Exact Representation of Sparse Networks with Symmetric Nonnegative Embeddings. - Sudhanshu Chanpuriya; Ryan A. Rossi; Anup B. Rao; Tung Mai; Nedim Lipka; Zhao Song 002; Cameron Musco (NeurIPS, 2023)

Finite Population Regression Adjustment and Non-asymptotic Guarantees for Treatment Effect Estimation. - Mehrdad Ghadiri; David Arbour; Tung Mai; Cameron Musco; Anup B. Rao (NeurIPS, 2023)

Brief Announcement: Dynamic Vector Bin Packing for Online Resource Allocation in the Cloud. - Aniket Murhekar; David Arbour; Tung Mai; Anup B. Rao (SPAA, 2023)

A Structural and Algorithmic Study of Stable Matching Lattices of Multiple Instances. - Rohith Reddy Gangam; Tung Mai; Nitya Raju; Vijay V. Vazirani (CoRR, 2023)

Dynamic Vector Bin Packing for Online Resource Allocation in the Cloud. - Aniket Murhekar; David Arbour; Tung Mai; Anup Rao 002 (CoRR, 2023)

Hallucination Diversity-Aware Active Learning for Text Summarization. - Yu Xia 007; Xu Liu; Tong Yu 001; Sungchul Kim; Ryan A. Rossi; Anup B. Rao; Tung Mai; Shuai Li 010 (NAACL-HLT, 2024)

Text-to-SQL Domain Adaptation via Human-LLM Collaborative Data Annotation. - Yuan Tian; Daniel Lee; Fei Wu; Tung Mai; Kun Qian 002; Siddhartha Sahai; Tianyi Zhang 001; Yunyao Li 001 (IUI, 2025)

CodeLutra: Boosting LLM Code Generation via Preference-Guided Refinement. - Leitian Tao; Xiang Chen; Tong Yu 001; Tung Mai; Ryan A. Rossi; Yixuan Li 001; Saayan Mitra (Trans. Mach. Learn. Res., 2025)

Detecting Ambiguities to Guide Query Rewrite for Robust Conversations in Enterprise AI Assistants. - Md. Mehrab Tanjim; Xiang Chen; Victor S. Bursztyn; Uttaran Bhattacharya; Tung Mai; Vaishnavi Muppala; Akash Maharaj; Saayan Mitra; Eunyee Koh; Yunyao Li 001; Ken Russell (CoRR, 2025)

From Documents to Dialogue: Building KG-RAG Enhanced AI Assistants. - Manisha Mukherjee; Sungchul Kim; Xiang Chen; Dan Luo; Tong Yu 001; Tung Mai (CoRR, 2025)