Ronak Mehta

According to our database, Ronak Mehta authored at least 24 papers between 2017 and 2025.

Collaborative distances:

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

2025

A Generalization Theory for Zero-Shot Prediction.

Ronak Mehta, Zaïd Harchaoui

CoRR, July, 2025

What do Large Language Models Say About Animals? Investigating Risks of Animal Harm in Generated Text.

Arturs Kanepajs, Aditi Basu, Sankalpa Ghose, Constance Li, Akshat Mehta, Ronak Mehta, Samuel David Tucker-Davis, Eric Zhou, Bob Fischer

CoRR, March, 2025

Proving the Coding Interview: A Benchmark for Formally Verified Code Generation.

Quinn Dougherty, Ronak Mehta

Proceedings of the IEEE/ACM International Workshop on Large Language Models for Code, 2025

What do Large Language Models Say About Animals? Investigating Risks of Animal Harm in Generated Text.

Arturs Kanepajs, Aditi Basu, Sankalpa Ghose, Constance Li, Akshat Mehta, Ronak Mehta, Samuel David Tucker-Davis, Bob Fischer, Jacy Reese Anthis

Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency, 2025

2024

A Primal-Dual Algorithm for Faster Distributionally Robust Optimization.

Ronak Mehta, Jelena Diakonikolas, Zaïd Harchaoui

CoRR, 2024

Drago: Primal-Dual Coupled Variance Reduction for Faster Distributionally Robust Optimization.

Ronak Mehta, Jelena Diakonikolas, Zaïd Harchaoui

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

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

Lang Liu, Ronak Mehta, Soumik Pal, Zaïd Harchaoui

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Distributionally Robust Optimization with Bias and Variance Reduction.

Ronak Mehta, Vincent Roulet, Krishna Pillutla, Zaïd Harchaoui

Proceedings of the Twelfth International Conference on Learning Representations, 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

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