Solving a Class of Non-Convex Min-Max Games Using Iterative First Order Methods. - Maher Nouiehed; Maziar Sanjabi; Tianjian Huang; Jason D. Lee; Meisam Razaviyayn (NeurIPS, 2019)

Non-convex Min-Max Optimization: Applications, Challenges, and Recent Theoretical Advances. - Meisam Razaviyayn; Tianjian Huang; Songtao Lu; Maher Nouiehed; Maziar Sanjabi; Mingyi Hong 001 (CoRR, 2020)

Nonconvex Min-Max Optimization: Applications, Challenges, and Recent Theoretical Advances. - Meisam Razaviyayn; Tianjian Huang; Songtao Lu; Maher Nouiehed; Maziar Sanjabi; Mingyi Hong 001 (IEEE Signal Process. Mag., 2020)

Alternating Direction Method of Multipliers for Quantization. - Tianjian Huang; Prajwal Singhania; Maziar Sanjabi; Pabitra Mitra; Meisam Razaviyayn (AISTATS, 2021)

DAIR: Data Augmented Invariant Regularization. - Tianjian Huang; Shaunak Ashish Halbe; Chinnadhurai Sankar; Pooyan Amini; Satwik Kottur; Alborz Geramifard; Meisam Razaviyayn; Ahmad Beirami (CoRR, 2021)

A decentralized adaptive momentum method for solving a class of min-max optimization problems. - Babak Barazandeh; Tianjian Huang; George Michailidis (Signal Process., 2021)

A Rigorous Study of Integrated Gradients Method and Extensions to Internal Neuron Attributions. - Daniel Lundström; Tianjian Huang; Meisam Razaviyayn (ICML, 2022)

Enhancing the precision of multi-parameter estimation for two-level open quantum system by mixed control. - Haiyuan Hong; Tianjian Huang; Xiujuan Lu; Sen Kuang (Quantum Inf. Process., 2022)

Mobile Application Privacy Risk Assessments from User-authored Scenarios. - Tianjian Huang; Vaishnavi Kaulagi; Mitra Bokaei Hosseini; Travis D. Breaux (RE, 2023)

Optimal Differentially Private Learning with Public Data. - Andrew Lowy; Zeman Li; Tianjian Huang; Meisam Razaviyayn (CoRR, 2023)

Robustness through Data Augmentation Loss Consistency. - Tianjian Huang; Shaunak Ashish Halbe; Chinnadhurai Sankar; Pooyan Amini; Satwik Kottur; Alborz Geramifard; Meisam Razaviyayn; Ahmad Beirami (Trans. Mach. Learn. Res., 2023)

Optimal Differentially Private Model Training with Public Data. - Andrew Lowy; Zeman Li; Tianjian Huang; Meisam Razaviyayn (ICML, 2024)