Balasubramanian, Krishnakumar

29 publications

COLT 2025 Online Covariance Estimation in Nonsmooth Stochastic Approximation Liwei Jiang, Abhishek Roy, Krishnakumar Balasubramanian, Damek Davis, Dmitriy Drusvyatskiy, Sen Na

NeurIPS 2024 A Separation in Heavy-Tailed Sampling: Gaussian vs. Stable Oracles for Proximal Samplers Ye He, Alireza Mousavi-Hosseini, Krishnakumar Balasubramanian, Murat A. Erdogdu

JMLR 2024 Mean-Square Analysis of Discretized Itô Diffusions for Heavy-Tailed Sampling Ye He, Tyler Farghly, Krishnakumar Balasubramanian, Murat A. Erdogdu

JMLR 2024 Optimal Algorithms for Stochastic Bilevel Optimization Under Relaxed Smoothness Conditions Xuxing Chen, Tesi Xiao, Krishnakumar Balasubramanian

NeurIPS 2024 Stochastic Optimization Algorithms for Instrumental Variable Regression with Streaming Data Xuxing Chen, Abhishek Roy, Yifan Hu, Krishnakumar Balasubramanian

UAI 2023 A One-Sample Decentralized Proximal Algorithm for Non-Convex Stochastic Composite Optimization Tesi Xiao, Xuxing Chen, Krishnakumar Balasubramanian, Saeed Ghadimi

NeurIPS 2023 Towards Understanding the Dynamics of Gaussian-Stein Variational Gradient Descent Tianle Liu, Promit Ghosal, Krishnakumar Balasubramanian, Natesh Pillai

NeurIPS 2022 A Projection-Free Algorithm for Constrained Stochastic Multi-Level Composition Optimization Tesi Xiao, Krishnakumar Balasubramanian, Saeed Ghadimi

NeurIPS 2022 Constrained Stochastic Nonconvex Optimization with State-Dependent Markov Data Abhishek Roy, Krishnakumar Balasubramanian, Saeed Ghadimi

JMLR 2022 Stochastic Zeroth-Order Optimization Under Nonstationarity and Nonconvexity Abhishek Roy, Krishnakumar Balasubramanian, Saeed Ghadimi, Prasant Mohapatra

JMLR 2022 Topologically Penalized Regression on Manifolds Olympio Hacquard, Krishnakumar Balasubramanian, Gilles Blanchard, Clément Levrard, Wolfgang Polonik

NeurIPS 2021 An Analysis of Constant Step Size SGD in the Non-Convex Regime: Asymptotic Normality and Bias Lu Yu, Krishnakumar Balasubramanian, Stanislav Volgushev, Murat A Erdogdu

JMLR 2021 Nonparametric Modeling of Higher-Order Interactions via Hypergraphons Krishnakumar Balasubramanian

NeurIPS 2021 On Empirical Risk Minimization with Dependent and Heavy-Tailed Data Abhishek Roy, Krishnakumar Balasubramanian, Murat A Erdogdu

JMLR 2021 On the Optimality of Kernel-Embedding Based Goodness-of-Fit Tests Krishnakumar Balasubramanian, Tong Li, Ming Yuan

NeurIPS 2020 Escaping Saddle-Point Faster Under Interpolation-like Conditions Abhishek Roy, Krishnakumar Balasubramanian, Saeed Ghadimi, Prasant Mohapatra

NeurIPS 2020 On the Ergodicity, Bias and Asymptotic Normality of Randomized Midpoint Sampling Method Ye He, Krishnakumar Balasubramanian, Murat A Erdogdu

COLT 2019 Normal Approximation for Stochastic Gradient Descent via Non-Asymptotic Rates of Martingale CLT Andreas Anastasiou, Krishnakumar Balasubramanian, Murat A. Erdogdu

NeurIPS 2018 Zeroth-Order (Non)-Convex Stochastic Optimization via Conditional Gradient and Gradient Updates Krishnakumar Balasubramanian, Saeed Ghadimi

NeurIPS 2017 Estimating High-Dimensional Non-Gaussian Multiple Index Models via Stein’s Lemma Zhuoran Yang, Krishnakumar Balasubramanian, Zhaoran Wang, Han Liu

ICML 2017 High-Dimensional Non-Gaussian Single Index Models via Thresholded Score Function Estimation Zhuoran Yang, Krishnakumar Balasubramanian, Han Liu

UAI 2013 High-Dimensional Joint Sparsity Random Effects Model for Multi-Task Learning Krishnakumar Balasubramanian, Kai Yu, Tong Zhang

ICML 2013 Smooth Sparse Coding via Marginal Regression for Learning Sparse Representations Krishnakumar Balasubramanian, Kai Yu, Guy Lebanon

AISTATS 2013 Ultrahigh Dimensional Feature Screening via RKHS Embeddings Krishnakumar Balasubramanian, Bharath K. Sriperumbudur, Guy Lebanon

ICML 2012 The Landmark Selection Method for Multiple Output Prediction Krishnakumar Balasubramanian, Guy Lebanon

JMLR 2011 Unsupervised Supervised Learning II: Margin-Based Classification Without Labels Krishnakumar Balasubramanian, Pinar Donmez, Guy Lebanon

AISTATS 2011 Unsupervised Supervised Learning II: Margin-Based Classification Without Labels Krishnakumar Balasubramanian, Pinar Donmez, Guy Lebanon

ICML 2010 Asymptotic Analysis of Generative Semi-Supervised Learning Joshua V. Dillon, Krishnakumar Balasubramanian, Guy Lebanon

JMLR 2010 Unsupervised Supervised Learning I: Estimating Classification and Regression Errors Without Labels Pinar Donmez, Guy Lebanon, Krishnakumar Balasubramanian