Publications

Conferences

The Benefits of Balance: From Information Projections to Variance Reduction
Lang Liu, Ronak Mehta, Soumik Pal, Zaid Harchaoui
NeurIPS, 2024.
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A Primal-Dual Algorithm for Faster Distributionally Robust Optimization
Ronak Mehta, Jelena Diakonikolas, Zaid Harchaoui
NeurIPS, 2024.
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Distributionally Robust Optimization with Bias and Variance Reduction
Ronak Mehta, Vincent Roulet, Krishna Pillutla, Zaid Harchaoui
ICLR, 2024 (Spotlight: top 5% of submissions).
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Stochastic Optimization for Spectral Risk Measures
Ronak Mehta, Vincent Roulet, Krishna Pillutla, Lang Liu, Zaid Harchaoui
AISTATS, 2023.
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Journals

Independence Testing for Temporal Data
Cencheng Shen, Jaewon Chung, Ronak Mehta, Ting Xu, Joshua T. Vogelstein
TMLR, 2024.
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Manifold Oblique Random Forests: Towards Closing the Gap on Convolutional Deep Networks
Adam Li, Ronan Perry, Chester Huynh, Tyler M. Tomita, Ronak Mehta, Jesus Arroyo, Jesse Patsolic, Ben Falk, Sridevi Sarma, and Joshua T. Vogelstein
SIAM Jour. Mathematics of Data Science, 2023.
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Workshops

GEANN: Scalable Graph Augmentations for Multi-Horizon Time Series Forecasting
Sitan Yang, Malcolm Wolff, Shankar Ramasubramanian, Vincent Quenneville-Belair, Ronak Mehta, Michael W. Mahoney
KDD Mining and Learning with Graphs, 2023.
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