Rahul Kidambi
Rahul Kidambi
Verified email at cornell.edu - Homepage
Title
Cited by
Cited by
Year
Parallelizing stochastic gradient descent for least squares regression: mini-batching, averaging, and model misspecification
P Jain, SM Kakade, R Kidambi, P Netrapalli, A Sidford
Journal of Machine Learning Research 18 (223), 1-42, 2018
67*2018
Accelerating stochastic gradient descent for least squares regression
P Jain, SM Kakade, R Kidambi, P Netrapalli, A Sidford
Conference On Learning Theory, 545-604, 2018
59*2018
On the insufficiency of existing momentum schemes for Stochastic Optimization
R Kidambi, P Netrapalli, P Jain, SM Kakade
arXiv preprint arXiv:1803.05591, 2018
312018
Submodular hamming metrics
JA Gillenwater, RK Iyer, B Lusch, R Kidambi, JA Bilmes
Advances in Neural Information Processing Systems, 3141-3149, 2015
142015
A Markov Chain Theory Approach to Characterizing the Minimax Optimality of Stochastic Gradient Descent (for Least Squares)
P Jain, SM Kakade, R Kidambi, P Netrapalli, VK Pillutla, A Sidford
arXiv preprint arXiv:1710.09430, 2017
112017
The Step Decay Schedule: A Near Optimal, Geometrically Decaying Learning Rate Procedure For Least Squares
R Ge, SM Kakade, R Kidambi, P Netrapalli
Advances in Neural Information Processing Systems, 14951-14962, 2019
10*2019
Leverage Score Sampling for Faster Accelerated Regression and ERM
N Agarwal, S Kakade, R Kidambi, YT Lee, P Netrapalli, A Sidford
arXiv preprint arXiv:1711.08426, 2017
92017
Deformable trellises on factor graphs for robust microtubule tracking in clutter
R Kidambi, MC Shih, K Rose
2012 9th IEEE International Symposium on Biomedical Imaging (ISBI), 676-679, 2012
52012
On shannon capacity and causal estimation
R Kidambi, S Kannan
2015 53rd Annual Allerton Conference on Communication, Control, and …, 2015
22015
Open Problem: Do Good Algorithms Necessarily Query Bad Points?
R Ge, P Jain, SM Kakade, R Kidambi, DM Nagaraj, P Netrapalli
Conference on Learning Theory, 3190-3193, 2019
12019
Efficient Estimation of Generalization Error and Bias-Variance Components of Ensembles
D Mahajan, V Gupta, SS Keerthi, S Sundararajan, S Narayanamurthy, ...
arXiv preprint arXiv:1711.05482, 2017
12017
Stochastic Gradient Descent For Modern Machine Learning: Theory, Algorithms And Applications
R Kidambi
2019
A Quantitative Evaluation Framework for Missing Value Imputation Algorithms
V Nair, R Kidambi, S Sellamanickam, SS Keerthi, J Gehrke, V Narayanan
arXiv preprint arXiv:1311.2276, 2013
2013
A Structured Prediction Approach for Missing Value Imputation
R Kidambi, V Nair, S Sellamanickam, SS Keerthi
arXiv preprint arXiv:1311.2137, 2013
2013
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Articles 1–14