Vamsi K. Potluru

Orcid: 0009-0000-6115-9777

According to our database1, Vamsi K. Potluru authored at least 33 papers between 2008 and 2024.

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Bibliography

2024
Six Levels of Privacy: A Framework for Financial Synthetic Data.
CoRR, 2024

Downstream Task-Oriented Generative Model Selections on Synthetic Data Training for Fraud Detection Models.
CoRR, 2024

Synthetic Data Applications in Finance.
CoRR, 2024

FairWASP: Fast and Optimal Fair Wasserstein Pre-processing.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Fair Wasserstein Coresets.
CoRR, 2023

On the Inherent Privacy Properties of Discrete Denoising Diffusion Models.
CoRR, 2023

GraphMaker: Can Diffusion Models Generate Large Attributed Graphs?
CoRR, 2023

Differentially private synthetic data using KD-trees.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

A supervised generative optimization approach for tabular data.
Proceedings of the 4th ACM International Conference on AI in Finance, 2023

Efficient Event Series Data Modeling via First-Order Constrained Optimization.
Proceedings of the 4th ACM International Conference on AI in Finance, 2023

Thresholded linear bandits.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Explicit Group Sparse Projection with Applications to Deep Learning and NMF.
Trans. Mach. Learn. Res., 2022

Fast Learning of Multidimensional Hawkes Processes via Frank-Wolfe.
CoRR, 2022

Differentially Private Learning of Hawkes Processes.
CoRR, 2022

Bandit Sampling for Multiplex Networks.
CoRR, 2022

Online Learning for Mixture of Multivariate Hawkes Processes.
Proceedings of the 3rd ACM International Conference on AI in Finance, 2022

2021
Graph Belief Propagation Networks.
CoRR, 2021

2020
Goal recognition via model-based and model-free techniques.
CoRR, 2020

Heuristics for Link Prediction in Multiplex Networks.
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.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Grouped sparse projection.
CoRR, 2019

Conservative Exploration using Interleaving.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2016
How to Fake Multiply by a Gaussian Matrix.
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.
NeuroImage, 2014

The tenth annual MLSP competition: Schizophrenia classification challenge.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2014

2013
Block Coordinate Descent for Sparse NMF
Proceedings of the 1st International Conference on Learning Representations, 2013

2012
Frugal Coordinate Descent for Large-Scale NNLS.
Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

2011
Correlated Noise: How it Breaks NMF, and What to Do About it.
J. Signal Process. Syst., 2011

Sparseness and a reduction from Totally Nonnegative Least Squares to SVM.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

Understanding and Exploiting the Connections between NMF and SVM.
Proceedings of the Data Mining Workshops (ICDMW), 2011

2009
Multiplicative updates For Non-Negative Kernel SVM
CoRR, 2009

Efficient Multiplicative Updates for Support Vector Machines.
Proceedings of the SIAM International Conference on Data Mining, 2009

2008
Group learning using contrast NMF : Application to functional and structural MRI of schizophrenia.
Proceedings of the International Symposium on Circuits and Systems (ISCAS 2008), 2008


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