Rahul Kidambi
Rahul Kidambi
在 cornell.edu 的电子邮件经过验证 - 首页
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引用次数
引用次数
年份
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
107*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
982018
Morel: Model-based offline reinforcement learning
R Kidambi, A Rajeswaran, P Netrapalli, T Joachims
arXiv preprint arXiv:2005.05951, 2020
942020
The step decay schedule: A near optimal, geometrically decaying learning rate procedure
R Ge, SM Kakade, R Kidambi, P Netrapalli
arXiv preprint arXiv:1904.12838, 2019
69*2019
On the insufficiency of existing momentum schemes for Stochastic Optimization
R Kidambi, P Netrapalli, P Jain, SM Kakade
arXiv preprint arXiv:1803.05591, 2018
662018
Submodular hamming metrics
J Gillenwater, R Iyer, B Lusch, R Kidambi, J Bilmes
arXiv preprint arXiv:1511.02163, 2015
162015
Leverage score sampling for faster accelerated regression and ERM
N Agarwal, S Kakade, R Kidambi, YT Lee, P Netrapalli, A Sidford
Algorithmic Learning Theory, 22-47, 2020
152020
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
142017
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
Making Paper Reviewing Robust to Bid Manipulation Attacks
R Wu, C Guo, F Wu, R Kidambi, L van der Maaten, KQ Weinberger
arXiv preprint arXiv:2102.06020, 2021
22021
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
22017
Mitigating Covariate Shift in Imitation Learning via Offline Data Without Great Coverage
JD Chang, M Uehara, D Sreenivas, R Kidambi, W Sun
arXiv preprint arXiv:2106.03207, 2021
12021
Top- eXtreme Contextual Bandits with Arm Hierarchy
R Sen, A Rakhlin, L Ying, R Kidambi, D Foster, D Hill, I Dhillon
arXiv preprint arXiv:2102.07800, 2021
12021
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
On shannon capacity and causal estimation
R Kidambi, S Kannan
2015 53rd Annual Allerton Conference on Communication, Control, and …, 2015
12015
MobILE: Model-Based Imitation Learning From Observation Alone
R Kidambi, J Chang, W Sun
arXiv preprint arXiv:2102.10769, 2021
2021
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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