Ronak Mehta

According to our database, Ronak Mehta authored at least 18 papers between 2017 and 2024.

Collaborative distances:

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

2024

A Primal-Dual Algorithm for Faster Distributionally Robust Optimization.

Ronak Mehta, Jelena Diakonikolas, Zaïd Harchaoui

CoRR, 2024

2023

Manifold Oblique Random Forests: Towards Closing the Gap on Convolutional Deep Networks.

Adam Li, Ronan Perry, Chester Huynh, Tyler M. Tomita, Ronak Mehta, Jesús Arroyo, Jesse Patsolic, Benjamin Falk, Sridevi V. Sarma, Joshua T. Vogelstein

SIAM J. Math. Data Sci., March, 2023

Distributionally Robust Optimization with Bias and Variance Reduction.

Ronak Mehta, Vincent Roulet, Krishna Pillutla, Zaïd Harchaoui

CoRR, 2023

Efficient Discrete Multi Marginal Optimal Transport Regularization.

Ronak Mehta, Jeffery Kline, Vishnu Suresh Lokhande, Glenn Fung, Vikas Singh

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Robustness and Convergence of Mirror Descent for Blind Deconvolution.

Ronak Mehta, Sathya N. Ravi, Vikas Singh

Proceedings of the IEEE International Conference on Acoustics, 2023

Stochastic Optimization for Spectral Risk Measures.

Ronak Mehta, Vincent Roulet, Krishna Pillutla, Lang Liu, Zaïd Harchaoui

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.

Anita Sinha, Ronak Mehta, Veena A. Nair, Rasmus M. Birn, Vikas Singh, Vivek Prabhakaran

Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

Deep Unlearning via Randomized Conditionally Independent Hessians.

Ronak Mehta, Sourav Pal, Vikas Singh, Sathya N. Ravi

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.

Jurijs Nazarovs, Ronak R. Mehta, Vishnu Suresh Lokhande, Vikas Singh

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

2019

Resource Constrained Neural Network Architecture Search.

Yunyang Xiong, Ronak Mehta, Vikas Singh

CoRR, 2019

Sampling-free Uncertainty Estimation in Gated Recurrent Units with Applications to Normative Modeling in Neuroimaging.

Seong Jae Hwang, Ronak Mehta, Hyunwoo J. Kim, Sterling C. Johnson, Vikas Singh

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

On Training Deep 3D CNN Models with Dependent Samples in Neuroimaging.

Yunyang Xiong, Hyunwoo J. Kim, Bhargav Tangirala, Ronak Mehta, Sterling C. Johnson, Vikas Singh

Proceedings of the Information Processing in Medical Imaging, 2019

Resource Constrained Neural Network Architecture Search: Will a Submodularity Assumption Help?

Yunyang Xiong, Ronak Mehta, Vikas Singh

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

DUAL-GLOW: Conditional Flow-Based Generative Model for Modality Transfer.

Haoliang Sun, Ronak Mehta, Hao Henry Zhou, Zhichun Huang, Sterling C. Johnson, Vivek Prabhakaran, Vikas Singh

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Scaling Recurrent Models via Orthogonal Approximations in Tensor Trains.

Ronak Mehta, Rudrasis Chakraborty, Vikas Singh, Yunyang Xiong

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018

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

Seong Jae Hwang, Ronak Mehta, Vikas Singh

CoRR, 2018

Robust Blind Deconvolution via Mirror Descent.

Sathya N. Ravi, Ronak Mehta, Vikas Singh

CoRR, 2018

2017

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

Ronak Mehta, Hyunwoo J. Kim, Shulei Wang, Sterling C. Johnson, Ming Yuan, Vikas Singh

CoRR, 2017