Ronak Mehta

According to our database1, Ronak Mehta authored at least 19 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2024
The Benefits of Balance: From Information Projections to Variance Reduction.
CoRR, 2024

A Primal-Dual Algorithm for Faster Distributionally Robust Optimization.
CoRR, 2024

Distributionally Robust Optimization with Bias and Variance Reduction.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Manifold Oblique Random Forests: Towards Closing the Gap on Convolutional Deep Networks.
SIAM J. Math. Data Sci., March, 2023

Efficient Discrete Multi Marginal Optimal Transport Regularization.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Robustness and Convergence of Mirror Descent for Blind Deconvolution.
Proceedings of the IEEE International Conference on Acoustics, 2023

Stochastic Optimization for Spectral Risk Measures.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Investigating Functional Brain Network Abnormalities via Differential Covariance Trajectory Analysis and Scan Statistics.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

Deep Unlearning via Randomized Conditionally Independent Hessians.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Graph reparameterizations for enabling 1000+ Monte Carlo iterations in Bayesian deep neural networks.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

2019
Resource Constrained Neural Network Architecture Search.
CoRR, 2019

Sampling-free Uncertainty Estimation in Gated Recurrent Units with Applications to Normative Modeling in Neuroimaging.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

On Training Deep 3D CNN Models with Dependent Samples in Neuroimaging.
Proceedings of the Information Processing in Medical Imaging, 2019

Resource Constrained Neural Network Architecture Search: Will a Submodularity Assumption Help?
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

DUAL-GLOW: Conditional Flow-Based Generative Model for Modality Transfer.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Scaling Recurrent Models via Orthogonal Approximations in Tensor Trains.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018
Sampling-free Uncertainty Estimation in Gated Recurrent Units with Exponential Families.
CoRR, 2018

Robust Blind Deconvolution via Mirror Descent.
CoRR, 2018

2017
Finding Differentially Covarying Needles in a Temporally Evolving Haystack: A Scan Statistics Perspective.
CoRR, 2017


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