Potluru, Vamsi K.

20 publications

AAAI 2025 Auditing and Enforcing Conditional Fairness via Optimal Transport Mohsen Ghassemi, Alan Mishler, Niccolò Dalmasso, Luhao Zhang, Vamsi K. Potluru, Tucker Balch, Manuela Veloso

UAI 2025 Distributionally and Adversarially Robust Logistic Regression via Intersecting Wasserstein Balls Aras Selvi, Eleonora Kreacic, Mohsen Ghassemi, Vamsi K. Potluru, Tucker Balch, Manuela Veloso

NeurIPS 2025 Do LLMs Really Forget? Evaluating Unlearning with Knowledge Correlation and Confidence Awareness Rongzhe Wei, Peizhi Niu, Hans Hao-Hsun Hsu, Ruihan Wu, Haoteng Yin, Mohsen Ghassemi, Yifan Li, Vamsi K. Potluru, Eli Chien, Kamalika Chaudhuri, Olgica Milenkovic, Pan Li

UAI 2025 Mixup Regularization: A Probabilistic Perspective Yousef El-Laham, Niccolo Dalmasso, Svitlana Vyetrenko, Vamsi K. Potluru, Manuela Veloso

ICML 2025 Underestimated Privacy Risks for Minority Populations in Large Language Model Unlearning Rongzhe Wei, Mufei Li, Mohsen Ghassemi, Eleonora Kreacic, Yifan Li, Xiang Yue, Bo Li, Vamsi K. Potluru, Pan Li, Eli Chien

NeurIPS 2024 Fair Wasserstein Coresets Zikai Xiong, Niccolò Dalmasso, Shubham Sharma, Freddy Lecue, Daniele Magazzeni, Vamsi K. Potluru, Tucker Balch, Manuela Veloso

AAAI 2024 FairWASP: Fast and Optimal Fair Wasserstein Pre-Processing Zikai Xiong, Niccolò Dalmasso, Alan Mishler, Vamsi K. Potluru, Tucker Balch, Manuela Veloso

TMLR 2024 GraphMaker: Can Diffusion Models Generate Large Attributed Graphs? Mufei Li, Eleonora Kreacic, Vamsi K. Potluru, Pan Li

ICLRW 2024 Guarding Multiple Secrets: Enhanced Summary Statistic Privacy for Data Sharing Shuaiqi Wang, Rongzhe Wei, Mohsen Ghassemi, Eleonora Kreacic, Vamsi K. Potluru

NeurIPSW 2024 Incentivized Exploration in Two-Sided Matching Markets Dung Daniel Ngo, Vamsi K. Potluru, Manuela Veloso

TMLR 2024 On the Inherent Privacy Properties of Discrete Denoising Diffusion Models Rongzhe Wei, Eleonora Kreacic, Haoyu Peter Wang, Haoteng Yin, Eli Chien, Vamsi K. Potluru, Pan Li

UAI 2023 Differentially Private Synthetic Data Using KD-Trees Eleonora Kreačić, Navid Nouri, Vamsi K. Potluru, Tucker Balch, Manuela Veloso

NeurIPSW 2023 Fair Wasserstein Coresets Zikai Xiong, Niccolo Dalmasso, Vamsi K. Potluru, Tucker Balch, Manuela Veloso

AISTATS 2023 Thresholded Linear Bandits Nishant A. Mehta, Junpei Komiyama, Vamsi K. Potluru, Andrea Nguyen, Mica Grant-Hagen

TMLR 2022 Explicit Group Sparse Projection with Applications to Deep Learning and NMF Riyasat Ohib, Nicolas Gillis, Niccolo Dalmasso, Sameena Shah, Vamsi K. Potluru, Sergey Plis

NeurIPSW 2022 Fast Learning of Multidimensional Hawkes Processes via Frank-Wolfe Renbo Zhao, Niccolo Dalmasso, Mohsen Ghassemi, Vamsi K. Potluru, Tucker Balch, Manuela Veloso

AISTATS 2020 Automatic Differentiation of Sketched Regression Hang Liao, Barak A. Pearlmutter, Vamsi K. Potluru, David P. Woodruff

AISTATS 2019 Conservative Exploration Using Interleaving Sumeet Katariya, Branislav Kveton, Zheng Wen, Vamsi K. Potluru

ICLR 2013 Block Coordinate Descent for Sparse NMF Vamsi K. Potluru, Sergey M. Plis, Jonathan Le Roux, Barak A. Pearlmutter, Vince D. Calhoun, Thomas P. Hayes

AAAI 2012 Frugal Coordinate Descent for Large-Scale NNLS Vamsi K. Potluru