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Krishnakumar Balasubramanian
Krishnakumar Balasubramanian
Verified email at ucdavis.edu - Homepage
Title
Cited by
Cited by
Year
The Landmark Selection Method for Multiple Output Prediction
K Balasubramanian, G Lebanon
Proc. of the 29th International Conference on Machine Learning (ICML), 2012
1122012
Zeroth-order (Non)-Convex Stochastic Optimization via Conditional Gradient and Gradient Updates
K Balasubramanian, S Ghadimi
Advances in Neural Information Processing Systems (NeurIPS), 2018
862018
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
692010
Zeroth-order Nonconvex Stochastic Optimization: Handling Constraints, High-Dimensionality and Saddle-Points
K Balasubramanian, S Ghadimi
Foundations of Computational Mathematics, 2022
602022
Smooth sparse coding via marginal regression for learning sparse representations
K Balasubramanian, K Yu, G Lebanon
International Conference on Machine Learning, 289-297, 2013
432013
Ultrahigh Dimensional Feature Screening via RKHS Embeddings
K Balasubramanian, BK Sriperumbudur, G Lebanon
International Conference on Artificial Intelligence and Statistics (AISTATS), 2013
412013
High-dimensional Non-Gaussian Single Index Models via Thresholded Score Function Estimation
HL Zhuoran Yang, Krishnakumar Balasubramanian
International Conference on Machine Learning, 2017
402017
Smooth Sparse Coding via Marginal Regression for Learning Sparse Representations
K Balasubramanian, K Yu, G Lebanon
Artificial Intelligence, 2016
402016
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
31*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
25*2011
Dimensionality reduction for text using domain knowledge
Y Mao, K Balasubramanian, G Lebanon
Coling 2010: Posters, 801-809, 2010
252010
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
22*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
222019
Zeroth-order algorithms for nonconvex–strongly-concave minimax problems with improved complexities
Z Wang, K Balasubramanian, S Ma, M Razaviyayn
Journal of Global Optimization (to appear), 2022
21*2022
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
202021
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
192021
Asymptotic analysis of generative semi-supervised learning
JV Dillon, K Balasubramanian, G Lebanon
International Conference on Machine Learning (ICML), 2010
172010
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
162017
Stochastic Zeroth-order Riemannian Derivative Estimation and Optimization
J Li, K Balasubramanian, S Ma
Mathematics of Operations Research, 2022
15*2022
Online and Bandit Algorithms for Nonstationary Stochastic Saddle-Point Optimization
A Roy, Y Chen, K Balasubramanian, P Mohapatra
arXiv preprint arXiv:1912.01698, 2019
142019
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Articles 1–20