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ORCIDVamsi K. Potluru
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2020 – today
- 2025
[c19]Mohsen Ghassemi, Alan Mishler, Niccolò Dalmasso, Luhao Zhang, Vamsi K. Potluru, Tucker Balch, Manuela Veloso:
Auditing and Enforcing Conditional Fairness via Optimal Transport. AAAI 2025: 16808-16816- [i27]Yousef El-Laham, Niccolò Dalmasso, Svitlana Vyetrenko, Vamsi K. Potluru, Manuela Veloso:
Mixup Regularization: A Probabilistic Perspective. CoRR abs/2502.13825 (2025) - [i26]Shayleen Reynolds, Saheed Obitayo, Niccolò Dalmasso, Dung Daniel T. Ngo, Vamsi K. Potluru, Manuela Veloso:
Toward Breaking Watermarks in Distortion-free Large Language Models. CoRR abs/2502.18608 (2025) - 2024
- [j4]Rongzhe Wei, Eleonora Kreacic, Haoyu Peter Wang, Haoteng Yin, Eli Chien, Vamsi K. Potluru, Pan Li:
On the Inherent Privacy Properties of Discrete Denoising Diffusion Models. Trans. Mach. Learn. Res. 2024 (2024) - [c18]Zikai Xiong, Niccolò Dalmasso, Alan Mishler, Vamsi K. Potluru, Tucker Balch, Manuela Veloso:
FairWASP: Fast and Optimal Fair Wasserstein Pre-processing. AAAI 2024: 16120-16128 - [c17]Zikai Xiong, Niccolò Dalmasso, Shubham Sharma, Freddy Lécué, Daniele Magazzeni, Vamsi K. Potluru, Tucker Balch, Manuela Veloso:
Fair Wasserstein Coresets. NeurIPS 2024 - [i25]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:
Synthetic Data Applications in Finance. CoRR abs/2401.00081 (2024) - [i24]Yinan Cheng, Chi-Hua Wang, Vamsi K. Potluru, Tucker Balch, Guang Cheng:
Downstream Task-Oriented Generative Model Selections on Synthetic Data Training for Fraud Detection Models. CoRR abs/2401.00974 (2024) - [i23]Tucker Balch, Vamsi K. Potluru, Deepak Paramanand, Manuela Veloso:
Six Levels of Privacy: A Framework for Financial Synthetic Data. CoRR abs/2403.14724 (2024) - [i22]Shuaiqi Wang, Rongzhe Wei, Mohsen Ghassemi, Eleonora Kreacic, Vamsi K. Potluru:
Guarding Multiple Secrets: Enhanced Summary Statistic Privacy for Data Sharing. CoRR abs/2405.13804 (2024) - [i21]Aras Selvi, Eleonora Kreacic, Mohsen Ghassemi, Vamsi K. Potluru, Tucker Balch, Manuela Veloso:
Distributionally and Adversarially Robust Logistic Regression via Intersecting Wasserstein Balls. CoRR abs/2407.13625 (2024) - [i20]Dung Daniel T. Ngo, Daniel Scott, Saheed Obitayo, Vamsi K. Potluru, Manuela Veloso:
Adaptive and Robust Watermark for Generative Tabular Data. CoRR abs/2409.14700 (2024) - [i19]Mohsen Ghassemi, Alan Mishler, Niccolò Dalmasso, Luhao Zhang, Vamsi K. Potluru, Tucker Balch, Manuela Veloso:
Auditing and Enforcing Conditional Fairness via Optimal Transport. CoRR abs/2410.14029 (2024) - [i18]Rongzhe Wei, Mufei Li, Mohsen Ghassemi, Eleonora Kreacic, Yifan Li, Xiang Yue, Bo Li, Vamsi K. Potluru, Pan Li, Eli Chien:
Underestimated Privacy Risks for Minority Populations in Large Language Model Unlearning. CoRR abs/2412.08559 (2024) - 2023
- [c16]Nishant A. Mehta, Junpei Komiyama, Vamsi K. Potluru, Andrea Nguyen, Mica Grant-Hagen:
Thresholded linear bandits. AISTATS 2023: 6968-7020 - [c15]Fadi Hamad
, Shinpei Nakamura-Sakai, Saheed Obitayo, Vamsi K. Potluru:
A supervised generative optimization approach for tabular data. ICAIF 2023: 10-18 - [c14]Niccolò Dalmasso, Renbo Zhao, Mohsen Ghassemi, Vamsi K. Potluru, Tucker Balch, Manuela Veloso:
Efficient Event Series Data Modeling via First-Order Constrained Optimization. ICAIF 2023: 463-471 - [c13]Eleonora Kreacic, Navid Nouri, Vamsi K. Potluru, Tucker Balch, Manuela Veloso:
Differentially private synthetic data using KD-trees. UAI 2023: 1143-1153 - [i17]Eleonora Kreacic, Navid Nouri, Vamsi K. Potluru, Tucker Balch, Manuela Veloso:
Differentially Private Synthetic Data Using KD-Trees. CoRR abs/2306.13211 (2023) - [i16]Fadi Hamad, Shinpei Nakamura-Sakai, Saheed Obitayo, Vamsi K. Potluru:
A supervised generative optimization approach for tabular data. CoRR abs/2309.05079 (2023) - [i15]Mufei Li, Eleonora Kreacic, Vamsi K. Potluru, Pan Li:
GraphMaker: Can Diffusion Models Generate Large Attributed Graphs? CoRR abs/2310.13833 (2023) - [i14]Rongzhe Wei, Eleonora Kreacic, Haoyu Wang, Haoteng Yin, Eli Chien, Vamsi K. Potluru, Pan Li:
On the Inherent Privacy Properties of Discrete Denoising Diffusion Models. CoRR abs/2310.15524 (2023) - [i13]Zikai Xiong, Niccolò Dalmasso, Alan Mishler, Vamsi K. Potluru, Tucker Balch, Manuela Veloso:
FairWASP: Fast and Optimal Fair Wasserstein Pre-processing. CoRR abs/2311.00109 (2023) - [i12]Zikai Xiong, Niccolò Dalmasso, Vamsi K. Potluru, Tucker Balch, Manuela Veloso:
Fair Wasserstein Coresets. CoRR abs/2311.05436 (2023) - 2022
- [j3]Riyasat Ohib, Nicolas Gillis, Niccolò Dalmasso, Sameena Shah, Vamsi K. Potluru, Sergey M. Plis:
Explicit Group Sparse Projection with Applications to Deep Learning and NMF. Trans. Mach. Learn. Res. 2022 (2022) - [c12]Mohsen Ghassemi, Niccolò Dalmasso, Simran Lamba, Vamsi K. Potluru, Tucker Balch, Sameena Shah, Manuela Veloso:
Online Learning for Mixture of Multivariate Hawkes Processes. ICAIF 2022: 506-513 - [i11]Cenk Baykal, Vamsi K. Potluru, Sameena Shah, Manuela M. Veloso:
Bandit Sampling for Multiplex Networks. CoRR abs/2202.03621 (2022) - [i10]Mohsen Ghassemi, Eleonora Kreacic, Niccolò Dalmasso, Vamsi K. Potluru, Tucker Balch, Manuela Veloso:
Differentially Private Learning of Hawkes Processes. CoRR abs/2207.13741 (2022) - [i9]Mohsen Ghassemi, Niccolò Dalmasso, Simran Lamba, Vamsi K. Potluru, Sameena Shah, Tucker Balch, Manuela Veloso:
Online Learning for Mixture of Multivariate Hawkes Processes. CoRR abs/2208.07961 (2022) - [i8]Renbo Zhao, Niccolò Dalmasso, Mohsen Ghassemi, Vamsi K. Potluru, Tucker Balch, Manuela Veloso:
Fast Learning of Multidimensional Hawkes Processes via Frank-Wolfe. CoRR abs/2212.06081 (2022) - 2021
- [i7]Junteng Jia, Cenk Baykal, Vamsi K. Potluru, Austin R. Benson:
Graph Belief Propagation Networks. CoRR abs/2106.03033 (2021) - 2020
- [c11]Hang Liao, Barak A. Pearlmutter, Vamsi K. Potluru, David P. Woodruff:
Automatic Differentiation of Sketched Regression. AISTATS 2020: 4367-4376 - [c10]Robert E. Tillman, Vamsi K. Potluru, Jiahao Chen, Prashant P. Reddy, Manuela Veloso:
Heuristics for Link Prediction in Multiplex Networks. ECAI 2020: 1938-1945 - [i6]Robert E. Tillman, Vamsi K. Potluru, Jiahao Chen, Prashant P. Reddy, Manuela M. Veloso:
Heuristics for Link Prediction in Multiplex Networks. CoRR abs/2004.04704 (2020) - [i5]Daniel Borrajo, Sriram Gopalakrishnan, Vamsi K. Potluru:
Goal recognition via model-based and model-free techniques. CoRR abs/2011.01832 (2020)
2010 – 2019
- 2019
- [c9]Sumeet Katariya, Branislav Kveton, Zheng Wen, Vamsi K. Potluru:
Conservative Exploration using Interleaving. AISTATS 2019: 954-963 - [i4]Nicolas Gillis, Riyasat Ohib, Sergey M. Plis, Vamsi K. Potluru:
Grouped sparse projection. CoRR abs/1912.03896 (2019) - 2018
- [i3]Sumeet Katariya, Branislav Kveton, Zheng Wen, Vamsi K. Potluru:
Conservative Exploration using Interleaving. CoRR abs/1806.00892 (2018) - 2016
- [c8]Michael Kapralov, Vamsi K. Potluru, David P. Woodruff:
How to Fake Multiply by a Gaussian Matrix. ICML 2016: 2101-2110 - [i2]Michael Kapralov, Vamsi K. Potluru, David P. Woodruff:
How to Fake Multiply by a Gaussian Matrix. CoRR abs/1606.05732 (2016) - 2014
- [j2]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:
High-order interactions observed in multi-task intrinsic networks are dominant indicators of aberrant brain function in schizophrenia. NeuroImage 102: 35-48 (2014) - [c7]Rogers F. Silva, Eduardo Castro, Cota Navin Gupta, Mustafa S. Çetin, Mohammad Arbabshirani, Vamsi K. Potluru, Sergey M. Plis, Vince D. Calhoun:
The tenth annual MLSP competition: Schizophrenia classification challenge. MLSP 2014: 1-6 - 2013
- [c6]Vamsi K. Potluru, Sergey M. Plis, Jonathan Le Roux, Barak A. Pearlmutter, Vince D. Calhoun, Thomas P. Hayes:
Block Coordinate Descent for Sparse NMF. ICLR (Poster) 2013 - 2012
- [c5]Vamsi K. Potluru:
Frugal Coordinate Descent for Large-Scale NNLS. AAAI 2012: 2451-2452 - 2011
- [j1]Sergey M. Plis, Vamsi K. Potluru, Terran Lane, Vince D. Calhoun:
Correlated Noise: How it Breaks NMF, and What to Do About it. J. Signal Process. Syst. 65(3): 351-359 (2011) - [c4]Vamsi K. Potluru:
Understanding and Exploiting the Connections between NMF and SVM. ICDM Workshops 2011: 1207-1210 - [c3]Vamsi K. Potluru, Sergey M. Plis, Shuang Luan, Vince D. Calhoun, Thomas P. Hayes:
Sparseness and a reduction from Totally Nonnegative Least Squares to SVM. IJCNN 2011: 1922-1929
2000 – 2009
- 2009
- [c2]Vamsi K. Potluru, Sergey M. Plis, Morten Mørup, Vincent D. Calhoun, Terran Lane:
Efficient Multiplicative Updates for Support Vector Machines. SDM 2009: 1220-1231 - [i1]Vamsi K. Potluru, Sergey M. Plis, Morten Mørup, Vince D. Calhoun, Terran Lane:
Multiplicative updates For Non-Negative Kernel SVM. CoRR abs/0902.4228 (2009) - 2008
- [c1]Vamsi K. Potluru, Vince D. Calhoun:
Group learning using contrast NMF : Application to functional and structural MRI of schizophrenia. ISCAS 2008: 1336-1339
Coauthor Index
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last updated on 2025-04-20 23:51 CEST by the dblp team
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