| The Landmark Selection Method for Multiple Output Prediction K Balasubramanian, G Lebanon Proc. of the 29th International Conference on Machine Learning (ICML), 2012 | 107 | 2012 |
| Zeroth-order (Non)-Convex Stochastic Optimization via Conditional Gradient and Gradient Updates K Balasubramanian, S Ghadimi Advances in Neural Information Processing Systems (NeurIPS), 2018 | 74 | 2018 |
| Unsupervised Supervised Learning I: Estimating Classification and Regression Errors without Labels. P Donmez, G Lebanon, K Balasubramanian Journal of Machine Learning Research 11 (4), 2010 | 62 | 2010 |
| Zeroth-order Nonconvex Stochastic Optimization: Handling Constraints, High-Dimensionality and Saddle-Points K Balasubramanian, S Ghadimi Foundations of Computational Mathematics, 2022 | 48 | 2022 |
| Smooth sparse coding via marginal regression for learning sparse representations K Balasubramanian, K Yu, G Lebanon International Conference on Machine Learning, 289-297, 2013 | 43 | 2013 |
| Smooth Sparse Coding via Marginal Regression for Learning Sparse Representations K Balasubramanian, K Yu, G Lebanon Artificial Intelligence, 2016 | 40 | 2016 |
| Ultrahigh Dimensional Feature Screening via RKHS Embeddings K Balasubramanian, BK Sriperumbudur, G Lebanon International Conference on Artificial Intelligence and Statistics (AISTATS), 2013 | 38 | 2013 |
| High-dimensional Non-Gaussian Single Index Models via Thresholded Score Function Estimation HL Zhuoran Yang, Krishnakumar Balasubramanian International Conference on Machine Learning, 2017 | 36 | 2017 |
| Learning Non-Gaussian Multi-Index Model via Second-Order Stein’s Method Z Yang, K Balasubramanian, Z Wang, H Liu Advances in Neural Information Processing Systems, 6099-6108, 2017 | 29* | 2017 |
| Unsupervised Supervised Learning II: Training Margin Based Classifiers without Labels. K Balasubramanian, P Donmez, G Lebanon Journal of Machine Learning Research 12, 1-30, 2011 | 24* | 2011 |
| Dimensionality reduction for text using domain knowledge Y Mao, K Balasubramanian, G Lebanon Coling 2010: Posters, 801-809, 2010 | 24 | 2010 |
| On the Optimality of Kernel-Embedding Based Goodness-of-Fit Tests. K Balasubramanian, T Li, M Yuan Journal of Machine Learning Research 22, 1:1-1:45, 2021 | 21* | 2021 |
| Normal Approximation for Stochastic Gradient Descent via Non-Asymptotic Rates of Martingale CLT A Anastasiou, K Balasubramanian, M Erdogdu Conference on Learning Theory, 2019 | 20 | 2019 |
| Zeroth-Order Algorithms for Nonconvex Minimax Problems with Improved Complexities Z Wang, K Balasubramanian, S Ma, M Razaviyayn Journal of Global Optimization (to appear), 2022 | 19 | 2022 |
| Asymptotic analysis of generative semi-supervised learning JV Dillon, K Balasubramanian, G Lebanon International Conference on Machine Learning (ICML), 2010 | 17 | 2010 |
| On Stein's Identity and Near-Optimal Estimation in High-dimensional Index Models Z Yang, K Balasubramanian, H Liu arXiv preprint arXiv:1709.08795, 2017 | 15 | 2017 |
| An Analysis of Constant Step Size SGD in the Non-convex Regime: Asymptotic Normality and Bias L Yu, K Balasubramanian, S Volgushev, MA Erdogdu 35th Conference on Neural Information Processing Systems (NeurIPS), 2021 | 14 | 2021 |
| Stochastic Multi-level Composition Optimization Algorithms with Level-Independent Convergence Rates K Balasubramanian, S Ghadimi, A Nguyen SIAM Journal on Optimization (to appear); arXiv preprint arXiv:2008.10526, 2021 | 13 | 2021 |
| Online and Bandit Algorithms for Nonstationary Stochastic Saddle-Point Optimization A Roy, Y Chen, K Balasubramanian, P Mohapatra arXiv preprint arXiv:1912.01698, 2019 | 13 | 2019 |
| Stochastic Zeroth-Order Optimization under Nonstationarity and Nonconvexity A Roy, K Balasubramanian, S Ghadimi, P Mohapatra Journal of Machine Learning Research 23 (64), 1-47, 2022 | 10* | 2022 |
