Ronak Mehta
10 papers · 2019–2025 · 6 venues · across top CS/AI venues
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🗺️ Taxonomy Completionist (20) 🌍 Conference Polyglot · Silver 🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge · Bronze 🏃 Academic Marathon · Sprint
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Century Club · Bronze
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Research topics
Machine Learning
(8)
Optimization & Theory
(6)
Learning Types · Machine Learning
(4)
Artificial Intelligence
(3)
Deep Learning
(3)
Mathematics & Optimization
(3)
Core AI
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Optimization
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Application Areas
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Computer Vision
(1)
Architectures
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Domain-Specific
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Learning Types · Deep Learning
(1)
Models
(1)
Keywords
linear convergence
(2)
distributionally robust optimization
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conditional independence
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variance reduction
(2)
neural architecture search
(1)
machine unlearning
(1)
stochastic gradient descent
(1)
discrete optimization
(1)
face recognition
(1)
risk minimization
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distribution shift
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strong convexity
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primal-dual algorithm
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hessian approximation
(1)
pet imaging
(1)
self-supervised learning
(1)
stochastic optimization
(1)
generalization
(1)
wasserstein metric
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submodular optimization
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Papers
A Generalization Theory for Zero-Shot Prediction
ICML 2025
Distributionally Robust Optimization with Bias and Variance Reduction
ICLR 2024
Drago: Primal-Dual Coupled Variance Reduction for Faster Distributionally Robust Optimization
NeurIPS 2024
The Benefits of Balance: From Information Projections to Variance Reduction
NeurIPS 2024
Efficient Discrete Multi Marginal Optimal Transport Regularization
ICLR 2023
Stochastic Optimization for Spectral Risk Measures
AISTATS 2023
Deep Unlearning via Randomized Conditionally Independent Hessians
CVPR 2022
DUAL-GLOW: Conditional Flow-Based Generative Model for Modality Transfer
ICCV 2019
Resource Constrained Neural Network Architecture Search: Will a Submodularity Assumption Help?
ICCV 2019
Scaling Recurrent Models via Orthogonal Approximations in Tensor Trains
ICCV 2019