Vamsi K. Potluru

According to our database, Vamsi K. Potluru authored at least 39 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

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

Trans. Mach. Learn. Res., 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, Eli Chien

CoRR, 2024

Auditing and Enforcing Conditional Fairness via Optimal Transport.

Mohsen Ghassemi, Alan Mishler, Niccolò Dalmasso, Luhao Zhang, Vamsi K. Potluru, Tucker Balch, Manuela Veloso

CoRR, 2024

Adaptive and Robust Watermark for Generative Tabular Data.

Dung Daniel Ngo, Daniel Scott, Saheed Obitayo, Vamsi K. Potluru, Manuela Veloso

CoRR, 2024

Distributionally and Adversarially Robust Logistic Regression via Intersecting Wasserstein Balls.

Aras Selvi, Eleonora Kreacic, Mohsen Ghassemi, Vamsi K. Potluru, Tucker Balch, 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

Six Levels of Privacy: A Framework for Financial Synthetic Data.

Tucker Balch, Vamsi K. Potluru, Deepak Paramanand, Manuela Veloso

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

CoRR, 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, Deepak Paramanand, Natraj Raman, Mikhail Solonin, Srijan Sood, Svitlana Vyetrenko, Haibei Zhu, Manuela Veloso, Tucker Balch

CoRR, 2024

FairWASP: Fast and Optimal Fair Wasserstein Pre-processing.

Zikai Xiong, Niccolò Dalmasso, Alan Mishler, Vamsi K. Potluru, Tucker Balch, Manuela Veloso

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Fair Wasserstein Coresets.

Zikai Xiong, Niccolò Dalmasso, Vamsi K. Potluru, Tucker Balch, Manuela Veloso

CoRR, 2023

On the Inherent Privacy Properties of Discrete Denoising Diffusion Models.

Rongzhe Wei, Eleonora Kreacic, Haoyu Wang, Haoteng Yin, Eli Chien, Vamsi K. Potluru, Pan Li

CoRR, 2023

GraphMaker: Can Diffusion Models Generate Large Attributed Graphs?

Mufei Li, Eleonora Kreacic, Vamsi K. Potluru, Pan Li

CoRR, 2023

Differentially private synthetic data using KD-trees.

Eleonora Kreacic, Navid Nouri, Vamsi K. Potluru, Tucker Balch, Manuela Veloso

Proceedings of the Uncertainty in Artificial Intelligence, 2023

A supervised generative optimization approach for tabular data.

Fadi Hamad, Shinpei Nakamura-Sakai, Saheed Obitayo, Vamsi K. Potluru

Proceedings of the 4th ACM International Conference on AI in Finance, 2023

Efficient Event Series Data Modeling via First-Order Constrained Optimization.

Niccolò Dalmasso, Renbo Zhao, Mohsen Ghassemi, Vamsi K. Potluru, Tucker Balch, Manuela Veloso

Proceedings of the 4th ACM International Conference on AI in Finance, 2023

Thresholded linear bandits.

Nishant A. Mehta, Junpei Komiyama, Vamsi K. Potluru, Andrea Nguyen, Mica Grant-Hagen

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

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

Fast Learning of Multidimensional Hawkes Processes via Frank-Wolfe.

Renbo Zhao, Niccolò Dalmasso, Mohsen Ghassemi, Vamsi K. Potluru, Tucker Balch, Manuela Veloso

CoRR, 2022

Differentially Private Learning of Hawkes Processes.

Mohsen Ghassemi, Eleonora Kreacic, Niccolò Dalmasso, Vamsi K. Potluru, Tucker Balch, Manuela Veloso

CoRR, 2022

Bandit Sampling for Multiplex Networks.

Cenk Baykal, Vamsi K. Potluru, Sameena Shah, Manuela M. Veloso

CoRR, 2022

Online Learning for Mixture of Multivariate Hawkes Processes.

Mohsen Ghassemi, Niccolò Dalmasso, Simran Lamba, Vamsi K. Potluru, Tucker Balch, Sameena Shah, Manuela Veloso

Proceedings of the 3rd ACM International Conference on AI in Finance, 2022

2021

Graph Belief Propagation Networks.

Junteng Jia, Cenk Baykal, Vamsi K. Potluru, Austin R. Benson

CoRR, 2021

2020

Goal recognition via model-based and model-free techniques.

Daniel Borrajo, Sriram Gopalakrishnan, Vamsi K. Potluru

CoRR, 2020

Heuristics for Link Prediction in Multiplex Networks.

Robert E. Tillman, Vamsi K. Potluru, Jiahao Chen, Prashant P. Reddy, Manuela Veloso

Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

Automatic Differentiation of Sketched Regression.

Hang Liao, Barak A. Pearlmutter, Vamsi K. Potluru, David P. Woodruff

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Grouped sparse projection.

Nicolas Gillis, Riyasat Ohib, Sergey M. Plis, Vamsi K. Potluru

CoRR, 2019

Conservative Exploration using Interleaving.

Sumeet Katariya, Branislav Kveton, Zheng Wen, Vamsi K. Potluru

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2016

How to Fake Multiply by a Gaussian Matrix.

Michael Kapralov, Vamsi K. Potluru, David P. Woodruff

Proceedings of the 33nd International Conference on Machine Learning, 2016

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

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

Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2014

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

Proceedings of the 1st International Conference on Learning Representations, 2013

2012

Frugal Coordinate Descent for Large-Scale NNLS.

Vamsi K. Potluru

Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

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

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

Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

Understanding and Exploiting the Connections between NMF and SVM.

Vamsi K. Potluru

Proceedings of the Data Mining Workshops (ICDMW), 2011

2009

Multiplicative updates For Non-Negative Kernel SVM

Vamsi K. Potluru, Sergey M. Plis, Morten Mørup, Vince D. Calhoun, Terran Lane

CoRR, 2009

Efficient Multiplicative Updates for Support Vector Machines.

Vamsi K. Potluru, Sergey M. Plis, Morten Mørup, Vincent D. Calhoun, Terran Lane

Proceedings of the SIAM International Conference on Data Mining, 2009

2008

Group learning using contrast NMF : Application to functional and structural MRI of schizophrenia.

Vamsi K. Potluru, Vince D. Calhoun

Proceedings of the International Symposium on Circuits and Systems (ISCAS 2008), 2008