Ronak Mehta - RankMe

32 papers A* 9A 2Misc 1Journal 16Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	A Generalization Theory for Zero-Shot Prediction. ICML Ronak Mehta, Zaïd Harchaoui
2025	J	`jnl`	A Generalization Theory for Zero-Shot Prediction. CoRR Ronak Mehta, Zaïd Harchaoui
2025	—	`conf`	Proving the Coding Interview: A Benchmark for Formally Verified Code Generation. LLM4Code@ICSE Quinn Dougherty, Ronak Mehta
2025	J	`jnl`	Proving the Coding Interview: A Benchmark for Formally Verified Code Generation. CoRR Quinn Dougherty, Ronak Mehta
2025	J	`jnl`	Stochastic Gradients under Nuisances. CoRR Facheng Yu, Ronak Mehta, Alex Luedtke, Zaïd Harchaoui
2025	J	`jnl`	Supervised Stochastic Gradient Algorithms for Multi-Trial Source Separation. CoRR Ronak Mehta, Mateus P. Otto, Noah Stanis, Azadeh Yazdan-Shahmorad, Zaïd Harchaoui
2025	—	`conf`	What do Large Language Models Say About Animals? Investigating Risks of Animal Harm in Generated Text. FAccT Arturs Kanepajs, Aditi Basu, Sankalpa Ghose, Constance Li, Akshat Mehta, Ronak Mehta, Samuel David Tucker-Davis, Bob Fischer, Jacy Reese Anthis
2025	J	`jnl`	What do Large Language Models Say About Animals? Investigating Risks of Animal Harm in Generated Text. CoRR Arturs Kanepajs, Aditi Basu, Sankalpa Ghose, Constance Li, Akshat Mehta, Ronak Mehta, Samuel David Tucker-Davis, Eric Zhou, Bob Fischer
2024	J	`jnl`	A Primal-Dual Algorithm for Faster Distributionally Robust Optimization. CoRR Ronak Mehta, Jelena Diakonikolas, Zaïd Harchaoui
2024	A*	`conf`	Distributionally Robust Optimization with Bias and Variance Reduction. ICLR Ronak Mehta, Vincent Roulet, Krishna Pillutla, Zaïd Harchaoui
2024	A*	`conf`	Drago: Primal-Dual Coupled Variance Reduction for Faster Distributionally Robust Optimization. NeurIPS Ronak Mehta, Jelena Diakonikolas, Zaïd Harchaoui
2024	A*	`conf`	The Benefits of Balance: From Information Projections to Variance Reduction. NeurIPS Lang Liu, Ronak Mehta, Soumik Pal, Zaïd Harchaoui
2024	J	`jnl`	The Benefits of Balance: From Information Projections to Variance Reduction. CoRR Lang Liu, Ronak Mehta, Soumik Pal, Zaïd Harchaoui
2023	J	`jnl`	Distributionally Robust Optimization with Bias and Variance Reduction. CoRR Ronak Mehta, Vincent Roulet, Krishna Pillutla, Zaïd Harchaoui
2023	A*	`conf`	Efficient Discrete Multi Marginal Optimal Transport Regularization. ICLR Ronak Mehta, Jeffery Kline, Vishnu Suresh Lokhande, Glenn Fung, Vikas Singh
2023	J	`jnl`	Manifold Oblique Random Forests: Towards Closing the Gap on Convolutional Deep Networks. SIAM J. Math. Data Sci. Adam Li, Ronan Perry, Chester Huynh, Tyler M. Tomita, Ronak Mehta, Jesús Arroyo, Jesse Patsolic, Benjamin Falk, Sridevi V. Sarma, Joshua T. Vogelstein
2023	Misc	`conf`	Robustness and Convergence of Mirror Descent for Blind Deconvolution. ICASSP Ronak Mehta, Sathya N. Ravi, Vikas Singh
2023	A	`conf`	Stochastic Optimization for Spectral Risk Measures. AISTATS Ronak Mehta, Vincent Roulet, Krishna Pillutla, Lang Liu, Zaïd Harchaoui
2022	A*	`conf`	Deep Unlearning via Randomized Conditionally Independent Hessians. CVPR Ronak Mehta, Sourav Pal, Vikas Singh, Sathya N. Ravi
2022	J	`jnl`	Deep Unlearning via Randomized Conditionally Independent Hessians. CoRR Ronak Mehta, Sourav Pal, Vikas Singh, Sathya N. Ravi
2022	—	`conf`	Investigating Functional Brain Network Abnormalities via Differential Covariance Trajectory Analysis and Scan Statistics. ISBI Anita Sinha, Ronak Mehta, Veena A. Nair, Rasmus M. Birn, Vikas Singh, Vivek Prabhakaran
2022	J	`jnl`	Stochastic Optimization for Spectral Risk Measures. CoRR Ronak Mehta, Vincent Roulet, Krishna Pillutla, Lang Liu, Zaïd Harchaoui
2019	A*	`conf`	DUAL-GLOW: Conditional Flow-Based Generative Model for Modality Transfer. ICCV Haoliang Sun, Ronak Mehta, Hao Henry Zhou, Zhichun Huang, Sterling C. Johnson, Vivek Prabhakaran, Vikas Singh
2019	J	`jnl`	DUAL-GLOW: Conditional Flow-Based Generative Model for Modality Transfer. CoRR Haoliang Sun, Ronak Mehta, Hao Henry Zhou, Zhichun Huang, Sterling C. Johnson, Vivek Prabhakaran, Vikas Singh
2019	—	`conf`	On Training Deep 3D CNN Models with Dependent Samples in Neuroimaging. IPMI Yunyang Xiong, Hyunwoo J. Kim, Bhargav Tangirala, Ronak Mehta, Sterling C. Johnson, Vikas Singh
2019	J	`jnl`	Resource Constrained Neural Network Architecture Search. CoRR Yunyang Xiong, Ronak Mehta, Vikas Singh
2019	A*	`conf`	Resource Constrained Neural Network Architecture Search: Will a Submodularity Assumption Help? ICCV Yunyang Xiong, Ronak Mehta, Vikas Singh
2019	A	`conf`	Sampling-free Uncertainty Estimation in Gated Recurrent Units with Applications to Normative Modeling in Neuroimaging. UAI Seong Jae Hwang, Ronak Mehta, Hyunwoo J. Kim, Sterling C. Johnson, Vikas Singh
2019	A*	`conf`	Scaling Recurrent Models via Orthogonal Approximations in Tensor Trains. ICCV Ronak Mehta, Rudrasis Chakraborty, Vikas Singh, Yunyang Xiong
2018	J	`jnl`	Robust Blind Deconvolution via Mirror Descent. CoRR Sathya N. Ravi, Ronak Mehta, Vikas Singh
2018	J	`jnl`	Sampling-free Uncertainty Estimation in Gated Recurrent Units with Exponential Families. CoRR Seong Jae Hwang, Ronak Mehta, Vikas Singh
2017	J	`jnl`	Finding Differentially Covarying Needles in a Temporally Evolving Haystack: A Scan Statistics Perspective. CoRR Ronak Mehta, Hyunwoo J. Kim, Shulei Wang, Sterling C. Johnson, Ming Yuan, Vikas Singh