| The Landmark Selection Method for Multiple Output Prediction K Balasubramanian, G Lebanon Proc. of the 29th International Conference on Machine Learning (ICML), 2012 | 84 | 2012 |
| Unsupervised supervised learning i: Estimating classification and regression errors without labels P Donmez, G Lebanon, K Balasubramanian Journal of Machine Learning Research 11 (Apr), 1323-1351, 2010 | 39 | 2010 |
| Smooth sparse coding via marginal regression for learning sparse representations K Balasubramanian, K Yu, G Lebanon International Conference on Machine Learning, 289-297, 2013 | 29 | 2013 |
| Ultrahigh Dimensional Feature Screening via RKHS Embeddings K Balasubramanian, BK Sriperumbudur, G Lebanon AISTATS, 2013 | 26 | 2013 |
| Zeroth-order (Non)-Convex Stochastic Optimization via Conditional Gradient and Gradient Updates K Balasubramanian, S Ghadimi Advances in Neural Information Processing Systems (NIPS), 2018 | 21 | 2018 |
| 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 | 20* | 2011 |
| Dimensionality reduction for text using domain knowledge Y Mao, K Balasubramanian, G Lebanon Proceedings of the 23rd International Conference on Computational …, 2010 | 19 | 2010 |
| High-dimensional Non-Gaussian Single Index Models via Thresholded Score Function Estimation HL Zhuoran Yang, Krishnakumar Balasubramanian International Conference on Machine Learning, 2017 | 16* | 2017 |
| Asymptotic analysis of generative semi-supervised learning JV Dillon, K Balasubramanian, G Lebanon Arxiv preprint arXiv:1003.0024, 2010 | 16 | 2010 |
| 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 | 11* | 2017 |
| Zeroth-order Nonconvex Stochastic Optimization: Handling Constraints, High-Dimensionality and Saddle-Points K Balasubramanian, S Ghadimi arXiv preprint arXiv:1809.06474v2, 2019 | 8 | 2019 |
| A fast algorithm for nonnegative tensor factorization using block coordinate descent and an active-set-type method K Balasubramanian, J Kim, A Puretskiy, MW Berry, H Park SIAM Text Mining, 2010 | 8 | 2010 |
| On the Optimality of Kernel-Embedding Based Goodness-of-Fit Tests K Balasubramanian, T Li, M Yuan arXiv preprint arXiv:1709.08148, 2017 | 7 | 2017 |
| 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 | 6 | 2017 |
| Smooth Sparse Coding via Marginal Regression for Learning Sparse Representations K Balasubramanian, K Yu, G Lebanon Artificial Intelligence, 2016 | 5 | 2016 |
| Non-asymptotic Results for Langevin Monte Carlo: Coordinate-wise and Black-box Sampling L Shen, K Balasubramanian, S Ghadimi arXiv preprint arxiv:1902.01373, 2019 | 2 | 2019 |
| Discussion: Estimating Structured High-Dimensional Covariance and Precision Matrices: Optimal Rates and Adaptive Estimation K Balasubramanian, M Yuan Electronic Journal of Statistics, 2016 | 2 | 2016 |
| High-dimensional Joint Sparsity Random Effects Model for Multi-task Learning K Balasubramanian, K Yu, T Zhang UAI, 2013 | 2 | 2013 |
| Online and Bandit Algorithms for Nonstationary Stochastic Saddle-Point Optimization A Roy, Y Chen, K Balasubramanian, P Mohapatra arXiv preprint arXiv:1912.01698, 2019 | 1 | 2019 |
| Multi-Point Bandit Algorithms for Nonstationary Online Nonconvex Optimization A Roy, K Balasubramanian, S Ghadimi, P Mohapatra arXiv preprint arXiv:1907.13616, 2019 | 1 | 2019 |
