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Adithya M. Devraj
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2020 – today
- 2022
- [j3]Adithya M. Devraj
, Sean P. Meyn
:
Q-Learning With Uniformly Bounded Variance. IEEE Trans. Autom. Control. 67(11): 5948-5963 (2022) - [i14]Yueyang Liu, Adithya M. Devraj, Benjamin Van Roy, Kuang Xu:
Gaussian Imagination in Bandit Learning. CoRR abs/2201.01902 (2022) - 2021
- [j2]Shuhang Chen, Adithya M. Devraj, Andrey Berstein, Sean P. Meyn:
Revisiting the ODE Method for Recursive Algorithms: Fast Convergence Using Quasi Stochastic Approximation. J. Syst. Sci. Complex. 34(5): 1681-1702 (2021) - [j1]Adithya M. Devraj
, Ioannis Kontoyiannis
, Sean P. Meyn
:
Differential Temporal Difference Learning. IEEE Trans. Autom. Control. 66(10): 4652-4667 (2021) - [c13]Shuhang Chen, Adithya M. Devraj, Andrey Bernstein, Sean P. Meyn:
Accelerating Optimization and Reinforcement Learning with Quasi Stochastic Approximation. ACC 2021: 1965-1972 - [i13]Adithya M. Devraj, Benjamin Van Roy, Kuang Xu:
A Bit Better? Quantifying Information for Bandit Learning. CoRR abs/2102.09488 (2021) - [i12]Vivek S. Borkar, Shuhang Chen, Adithya M. Devraj, Ioannis Kontoyiannis, Sean P. Meyn:
The ODE Method for Asymptotic Statistics in Stochastic Approximation and Reinforcement Learning. CoRR abs/2110.14427 (2021) - 2020
- [c12]Shuhang Chen, Adithya M. Devraj, Ana Busic, Sean P. Meyn:
Explicit Mean-Square Error Bounds for Monte-Carlo and Linear Stochastic Approximation. AISTATS 2020: 4173-4183 - [c11]Naren Srivaths Raman, Adithya M. Devraj, Prabir Barooah, Sean P. Meyn:
Reinforcement Learning for Control of Building HVAC Systems. ACC 2020: 2326-2332 - [c10]Yue Chen, Andrey Bernstein, Adithya M. Devraj, Sean P. Meyn:
Model-Free Primal-Dual Methods for Network Optimization with Application to Real-Time Optimal Power Flow. ACC 2020: 3140-3147 - [c9]Shuhang Chen, Adithya M. Devraj, Ana Busic
, Sean P. Meyn:
Zap Q-Learning for Optimal Stopping. ACC 2020: 3920-3925 - [c8]Shuhang Chen, Adithya M. Devraj, Fan Lu, Ana Busic, Sean P. Meyn:
Zap Q-Learning With Nonlinear Function Approximation. NeurIPS 2020 - [i11]Shuhang Chen, Adithya M. Devraj, Ana Busic, Sean P. Meyn:
Explicit Mean-Square Error Bounds for Monte-Carlo and Linear Stochastic Approximation. CoRR abs/2002.02584 (2020) - [i10]Adithya M. Devraj, Sean P. Meyn:
Q-learning with Uniformly Bounded Variance: Large Discounting is Not a Barrier to Fast Learning. CoRR abs/2002.10301 (2020) - [i9]Shuhang Chen, Adithya M. Devraj, Andrey Bernstein, Sean P. Meyn:
Accelerating Optimization and Reinforcement Learning with Quasi-Stochastic Approximation. CoRR abs/2009.14431 (2020)
2010 – 2019
- 2019
- [c7]Adithya M. Devraj, Ana Busic, Sean P. Meyn:
On Matrix Momentum Stochastic Approximation and Applications to Q-learning. Allerton 2019: 749-756 - [c6]Adithya M. Devraj, Jianshu Chen:
Stochastic Variance Reduced Primal Dual Algorithms for Empirical Composition Optimization. NeurIPS 2019: 9878-9888 - [i8]Shuhang Chen, Adithya M. Devraj, Ana Busic, Sean P. Meyn:
Zap~Q-Learning for Optimal Stopping Time Problems. CoRR abs/1904.11538 (2019) - [i7]Adithya M. Devraj, Jianshu Chen:
Stochastic Variance Reduced Primal Dual Algorithms for Empirical Composition Optimization. CoRR abs/1907.09150 (2019) - [i6]Yue Chen, Andrey Bernstein, Adithya M. Devraj, Sean P. Meyn:
Model-Free Primal-Dual Methods for Network Optimization with Application to Real-Time Optimal Power Flow. CoRR abs/1909.13132 (2019) - [i5]Shuhang Chen, Adithya M. Devraj, Ana Busic, Sean P. Meyn:
Zap Q-Learning With Nonlinear Function Approximation. CoRR abs/1910.05405 (2019) - 2018
- [i4]Adithya M. Devraj, Ana Busic, Sean P. Meyn:
Zap Meets Momentum: Stochastic Approximation Algorithms with Optimal Convergence Rate. CoRR abs/1809.06277 (2018) - [i3]Adithya M. Devraj, Ioannis Kontoyiannis, Sean P. Meyn:
Differential Temporal Difference Learning. CoRR abs/1812.11137 (2018) - 2017
- [c5]Adithya M. Devraj, Sean P. Meyn:
Zap Q-Learning. NIPS 2017: 2235-2244 - [i2]Adithya M. Devraj, Sean P. Meyn:
Fastest Convergence for Q-learning. CoRR abs/1707.03770 (2017) - 2016
- [c4]Anand Radhakrishnan, Adithya M. Devraj, Sean P. Meyn:
Learning techniques for feedback particle filter design. CDC 2016: 5453-5459 - [c3]Adithya M. Devraj, Sean P. Meyn:
Differential TD learning for value function approximation. CDC 2016: 6347-6354 - [i1]Adithya M. Devraj, Sean P. Meyn:
Differential TD Learning for Value Function Approximation. CoRR abs/1604.01828 (2016) - 2015
- [c2]Adithya M. Devraj, Chris Gianelli, Jian Li:
Array processing with known waveform and steering vector but unknown diagonal noise covariance matrix. CAMSAP 2015: 105-108 - 2014
- [c1]Adithya M. Devraj, Mohit K. Sharma
, Chandra R. Murthy
:
Power allocation in energy harvesting sensors with ARQ: A convex optimization approach. GlobalSIP 2014: 208-212
Coauthor Index
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