Group learning using contrast NMF : Application to functional and structural MRI of schizophrenia. - Vamsi K. Potluru; Vince D. Calhoun (ISCAS, 2008)

Efficient Multiplicative Updates for Support Vector Machines. - Vamsi K. Potluru; Sergey M. Plis; Morten Mørup; Vincent D. Calhoun; Terran Lane (SDM, 2009)

Multiplicative updates For Non-Negative Kernel SVM - Vamsi K. Potluru; Sergey M. Plis; Morten Mørup; Vince D. Calhoun; Terran Lane (CoRR, 2009)

Understanding and Exploiting the Connections between NMF and SVM. - Vamsi K. Potluru (ICDM Workshops, 2011)

Sparseness and a reduction from Totally Nonnegative Least Squares to SVM. - Vamsi K. Potluru; Sergey M. Plis; Shuang Luan; Vince D. Calhoun; Thomas P. Hayes (IJCNN, 2011)

Correlated Noise: How it Breaks NMF, and What to Do About it. - Sergey M. Plis; Vamsi K. Potluru; Terran Lane; Vince D. Calhoun (J. Signal Process. Syst., 2011)

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

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

The tenth annual MLSP competition: Schizophrenia classification challenge. - Rogers F. Silva; Eduardo Castro; Cota Navin Gupta; Mustafa S. Çetin; Mohammad Arbabshirani; Vamsi K. Potluru; Sergey M. Plis; Vince D. Calhoun (MLSP, 2014)

High-order interactions observed in multi-task intrinsic networks are dominant indicators of aberrant brain function in schizophrenia. - Sergey M. Plis; Jing Sui; Terran Lane; Sushmita Roy; Vincent P. Clark; Vamsi K. Potluru; René J. Huster; Andrew Michael; Scott R. Sponheim; Michael P. Weisend; Vince D. Calhoun (NeuroImage, 2014)

How to Fake Multiply by a Gaussian Matrix. - Michael Kapralov; Vamsi K. Potluru; David P. Woodruff (ICML, 2016)

Conservative Exploration using Interleaving. - Sumeet Katariya; Branislav Kveton; Zheng Wen; Vamsi K. Potluru (AISTATS, 2019)

Grouped sparse projection. - Nicolas Gillis; Riyasat Ohib; Sergey M. Plis; Vamsi K. Potluru (CoRR, 2019)

Automatic Differentiation of Sketched Regression. - Hang Liao 001; Barak A. Pearlmutter; Vamsi K. Potluru; David P. Woodruff (AISTATS, 2020)

Heuristics for Link Prediction in Multiplex Networks. - Robert E. Tillman; Vamsi K. Potluru; Jiahao Chen 001; Prashant P. Reddy; Manuela Veloso (ECAI, 2020)

Goal recognition via model-based and model-free techniques. - Daniel Borrajo; Sriram Gopalakrishnan; Vamsi K. Potluru (CoRR, 2020)

Graph Belief Propagation Networks. - Junteng Jia; Cenk Baykal; Vamsi K. Potluru; Austin R. Benson (CoRR, 2021)

Online Learning for Mixture of Multivariate Hawkes Processes. - Mohsen Ghassemi; Niccolò Dalmasso; Simran Lamba; Vamsi K. Potluru; Tucker Balch; Sameena Shah; Manuela Veloso (ICAIF, 2022)

Bandit Sampling for Multiplex Networks. - Cenk Baykal; Vamsi K. Potluru; Sameena Shah; Manuela M. Veloso (CoRR, 2022)

Differentially Private Learning of Hawkes Processes. - Mohsen Ghassemi; Eleonora Kreacic; Niccolò Dalmasso; Vamsi K. Potluru; Tucker Balch; Manuela Veloso (CoRR, 2022)

Fast Learning of Multidimensional Hawkes Processes via Frank-Wolfe. - Renbo Zhao; Niccolò Dalmasso; Mohsen Ghassemi; Vamsi K. Potluru; Tucker Balch; Manuela Veloso (CoRR, 2022)

Explicit Group Sparse Projection with Applications to Deep Learning and NMF. - Riyasat Ohib; Nicolas Gillis; Niccolò Dalmasso; Sameena Shah; Vamsi K. Potluru; Sergey M. Plis (Trans. Mach. Learn. Res., 2022)

Thresholded linear bandits. - Nishant A. Mehta; Junpei Komiyama; Vamsi K. Potluru; Andrea Nguyen; Mica Grant-Hagen (AISTATS, 2023)

Efficient Event Series Data Modeling via First-Order Constrained Optimization. - Niccolò Dalmasso; Renbo Zhao; Mohsen Ghassemi; Vamsi K. Potluru; Tucker Balch; Manuela Veloso (ICAIF, 2023)

A supervised generative optimization approach for tabular data. - Fadi Hamad; Shinpei Nakamura-Sakai; Saheed Obitayo; Vamsi K. Potluru (ICAIF, 2023)

Differentially private synthetic data using KD-trees. - Eleonora Kreacic; Navid Nouri; Vamsi K. Potluru; Tucker Balch; Manuela Veloso (UAI, 2023)

On the Inherent Privacy Properties of Discrete Denoising Diffusion Models. - Rongzhe Wei; Eleonora Kreacic; Haoyu Wang 004; Haoteng Yin; Eli Chien; Vamsi K. Potluru; Pan Li 005 (CoRR, 2023)

Fair Wasserstein Coresets. - Zikai Xiong; Niccolò Dalmasso; Vamsi K. Potluru; Tucker Balch; Manuela Veloso (CoRR, 2023)

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

Fair Wasserstein Coresets. - Zikai Xiong; Niccolò Dalmasso; Shubham Sharma; Freddy Lécué; Daniele Magazzeni; Vamsi K. Potluru; Tucker Balch; Manuela Veloso (NeurIPS, 2024)

Synthetic Data Applications in Finance. - Vamsi K. Potluru; Daniel Borrajo; Andrea Coletta; Niccolò Dalmasso; Yousef El-Laham; Elizabeth Fons; Mohsen Ghassemi; Sriram Gopalakrishnan; Vikesh Gosai; Eleonora Kreacic; Ganapathy Mani; Saheed Obitayo; et al. (CoRR, 2024)

Downstream Task-Oriented Generative Model Selections on Synthetic Data Training for Fraud Detection Models. - Yinan Cheng; Chi-Hua Wang; Vamsi K. Potluru; Tucker Balch; Guang Cheng 003 (CoRR, 2024)

Six Levels of Privacy: A Framework for Financial Synthetic Data. - Tucker Balch; Vamsi K. Potluru; Deepak Paramanand; Manuela Veloso (CoRR, 2024)

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

Adaptive and Robust Watermark for Generative Tabular Data. - Dung Daniel T. Ngo; Daniel Scott; Saheed Obitayo; Vamsi K. Potluru; Manuela Veloso (CoRR, 2024)

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 005; Eli Chien (CoRR, 2024)

GraphMaker: Can Diffusion Models Generate Large Attributed Graphs? - Mufei Li; Eleonora Kreacic; Vamsi K. Potluru; Pan Li 005 (Trans. Mach. Learn. Res., 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 005 (Trans. Mach. Learn. Res., 2024)

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

Mixup Regularization: A Probabilistic Perspective. - Yousef El-Laham; Niccolò Dalmasso; Svitlana Vyetrenko; Vamsi K. Potluru; 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 (UAI, 2025)

Toward Breaking Watermarks in Distortion-free Large Language Models. - Shayleen Reynolds; Saheed Obitayo; Niccolò Dalmasso; Dung Daniel T. Ngo; Vamsi K. Potluru; Manuela Veloso (CoRR, 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 005 (CoRR, 2025)