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ORCIDRonak Mehta
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2020 – today
- 2024
[c14]Ronak Mehta, Vincent Roulet, Krishna Pillutla, Zaïd Harchaoui:
Distributionally Robust Optimization with Bias and Variance Reduction. ICLR 2024- [c13]Lang Liu, Ronak Mehta, Soumik Pal, Zaïd Harchaoui:
The Benefits of Balance: From Information Projections to Variance Reduction. NeurIPS 2024 - [c12]Ronak Mehta, Jelena Diakonikolas, Zaïd Harchaoui:
Drago: Primal-Dual Coupled Variance Reduction for Faster Distributionally Robust Optimization. NeurIPS 2024 - [i11]Ronak Mehta, Jelena Diakonikolas, Zaïd Harchaoui:
A Primal-Dual Algorithm for Faster Distributionally Robust Optimization. CoRR abs/2403.10763 (2024) - [i10]Lang Liu, Ronak Mehta, Soumik Pal, Zaïd Harchaoui:
The Benefits of Balance: From Information Projections to Variance Reduction. CoRR abs/2408.15065 (2024) - 2023
- [j1]Adam Li
, Ronan Perry, Chester Huynh, Tyler M. Tomita, Ronak Mehta, Jesús Arroyo, Jesse Patsolic, Benjamin Falk, Sridevi V. Sarma, Joshua T. Vogelstein:
Manifold Oblique Random Forests: Towards Closing the Gap on Convolutional Deep Networks. SIAM J. Math. Data Sci. 5(1): 77-96 (2023) - [c11]Ronak Mehta, Vincent Roulet, Krishna Pillutla, Lang Liu, Zaïd Harchaoui:
Stochastic Optimization for Spectral Risk Measures. AISTATS 2023: 10112-10159 - [c10]Ronak Mehta, Sathya N. Ravi, Vikas Singh:
Robustness and Convergence of Mirror Descent for Blind Deconvolution. ICASSP 2023: 1-5 - [c9]Ronak Mehta, Jeffery Kline, Vishnu Suresh Lokhande, Glenn Fung, Vikas Singh:
Efficient Discrete Multi Marginal Optimal Transport Regularization. ICLR 2023 - [i9]Ronak Mehta, Vincent Roulet, Krishna Pillutla, Zaïd Harchaoui:
Distributionally Robust Optimization with Bias and Variance Reduction. CoRR abs/2310.13863 (2023) - 2022
- [c8]Ronak Mehta, Sourav Pal, Vikas Singh, Sathya N. Ravi:
Deep Unlearning via Randomized Conditionally Independent Hessians. CVPR 2022: 10412-10421 - [c7]Anita Sinha, Ronak Mehta, Veena A. Nair, Rasmus M. Birn, Vikas Singh, Vivek Prabhakaran:
Investigating Functional Brain Network Abnormalities via Differential Covariance Trajectory Analysis and Scan Statistics. ISBI 2022: 1-4 - [i8]Jurijs Nazarovs, Ronak R. Mehta, Vishnu Suresh Lokhande, Vikas Singh:
Graph Reparameterizations for Enabling 1000+ Monte Carlo Iterations in Bayesian Deep Neural Networks. CoRR abs/2202.09478 (2022) - [i7]Ronak Mehta, Sourav Pal, Vikas Singh, Sathya N. Ravi:
Deep Unlearning via Randomized Conditionally Independent Hessians. CoRR abs/2204.07655 (2022) - [i6]Ronak Mehta, Vincent Roulet, Krishna Pillutla, Lang Liu, Zaïd Harchaoui:
Stochastic Optimization for Spectral Risk Measures. CoRR abs/2212.05149 (2022) - 2021
- [c6]Jurijs Nazarovs, Ronak R. Mehta, Vishnu Suresh Lokhande, Vikas Singh:
Graph reparameterizations for enabling 1000+ Monte Carlo iterations in Bayesian deep neural networks. UAI 2021: 118-128
2010 – 2019
- 2019
- [c5]Yunyang Xiong, Ronak Mehta, Vikas Singh:
Resource Constrained Neural Network Architecture Search: Will a Submodularity Assumption Help? ICCV 2019: 1901-1910 - [c4]Ronak Mehta, Rudrasis Chakraborty, Vikas Singh, Yunyang Xiong:
Scaling Recurrent Models via Orthogonal Approximations in Tensor Trains. ICCV 2019: 10570-10578 - [c3]Haoliang Sun, Ronak Mehta, Hao Henry Zhou, Zhichun Huang, Sterling C. Johnson, Vivek Prabhakaran, Vikas Singh:
DUAL-GLOW: Conditional Flow-Based Generative Model for Modality Transfer. ICCV 2019: 10610-10619 - [c2]Yunyang Xiong, Hyunwoo J. Kim, Bhargav Tangirala, Ronak Mehta, Sterling C. Johnson, Vikas Singh:
On Training Deep 3D CNN Models with Dependent Samples in Neuroimaging. IPMI 2019: 99-111 - [c1]Seong Jae Hwang, Ronak Mehta, Hyunwoo J. Kim, Sterling C. Johnson, Vikas Singh:
Sampling-free Uncertainty Estimation in Gated Recurrent Units with Applications to Normative Modeling in Neuroimaging. UAI 2019: 809-819 - [i5]Yunyang Xiong, Ronak Mehta, Vikas Singh:
Resource Constrained Neural Network Architecture Search. CoRR abs/1904.03786 (2019) - [i4]Haoliang Sun, Ronak Mehta, Hao Henry Zhou, Zhichun Huang, Sterling C. Johnson, Vivek Prabhakaran, Vikas Singh:
DUAL-GLOW: Conditional Flow-Based Generative Model for Modality Transfer. CoRR abs/1908.08074 (2019) - 2018
- [i3]Sathya N. Ravi, Ronak Mehta, Vikas Singh:
Robust Blind Deconvolution via Mirror Descent. CoRR abs/1803.08137 (2018) - [i2]Seong Jae Hwang, Ronak Mehta, Vikas Singh:
Sampling-free Uncertainty Estimation in Gated Recurrent Units with Exponential Families. CoRR abs/1804.07351 (2018) - 2017
- [i1]Ronak Mehta, Hyunwoo J. Kim, Shulei Wang, Sterling C. Johnson, Ming Yuan, Vikas Singh:
Finding Differentially Covarying Needles in a Temporally Evolving Haystack: A Scan Statistics Perspective. CoRR abs/1711.07575 (2017)
Coauthor Index
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