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Alec Koppel
Alec Koppel
AI Research Lead, JP Morgan AI Research
Verified email at jpmchase.com - Homepage
Title
Cited by
Cited by
Year
A saddle point algorithm for networked online convex optimization
A Koppel, FY Jakubiec, A Ribeiro
IEEE Transactions on Signal Processing 63 (19), 5149-5164, 2015
1542015
Global convergence of policy gradient methods to (almost) locally optimal policies
K Zhang, A Koppel, H Zhu, T Basar
SIAM Journal on Control and Optimization 58 (6), 3586-3612, 2020
1322020
A Class of Prediction-Correction Methods for Time-Varying Convex Optimization
A Simonetto, A Mokhtari, A Koppel, G Leus, A Ribeiro
IEEE Transactions on Signal Processing (submitted), 0
114*
Proximity without consensus in online multi-agent optimization
A Koppel, BM Sadler, A Ribeiro
Proc. Int. Conf. Accoustics Speech Signal Proces (submitted),, 2016
782016
Variational policy gradient method for reinforcement learning with general utilities
J Zhang, A Koppel, AS Bedi, C Szepesvari, M Wang
Advances in Neural Information Processing Systems 33, 4572-4583, 2020
722020
A Decentralized Prediction-Correction Method for Networked Time-Varying Convex Optimization
A Simonetto, A Mokhtari, A Koppel, G Leus, A Ribeiro
Computational Advances in Multi-Sensor Adaptive Processing, IEEE …, 2015
692015
On the sample complexity of actor-critic method for reinforcement learning with function approximation
H Kumar, A Koppel, A Ribeiro
arXiv preprint arXiv:1910.08412, 2019
582019
Decentralized online learning with kernels
A Koppel, S Paternain, C Richard, A Ribeiro
IEEE Transactions on Signal Processing 66 (12), 3240-3255, 2018
542018
Parsimonious online learning with kernels via sparse projections in function space
A Koppel, G Warnell, E Stump, A Ribeiro
The Journal of Machine Learning Research 20 (1), 83-126, 2019
47*2019
D4L: Decentralized Dynamic Discrminative Dictionary Learning
A Koppel, G Warnell, E Stump, A Ribeiro
IEEE Transactions on Signal and Info. Processing over Networks, 2015
402015
Parsimonious online learning with kernels via sparse projections in function space
A Koppel, G Warnell, E Stump, A Ribeiro
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
372017
Consistent online gaussian process regression without the sample complexity bottleneck
A Koppel, H Pradhan, K Rajawat
Statistics and Computing 31, 1-18, 2021
262021
Policy Evaluation in Continuous MDPs with Efficient Kernelized Gradient Temporal Difference
A Koppel, G Warnell, E Stump, P Stone, A Ribeiro.
IEEE Transactions on Automatic Control 66 (4), 2020
26*2020
Online learning for characterizing unknown environments in ground robotic vehicle models
A Koppel, J Fink, G Warnell, E Stump, A Ribeiro
2016 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2016
252016
Projected Stochastic Primal-Dual Method for Constrained Online Learning with Kernels
A Koppel, K Zhang, H Zhu, TM Baser.
IEEE Trans. Signal Processing (submitted), 2018
212018
Cautious reinforcement learning via distributional risk in the dual domain
J Zhang, AS Bedi, M Wang, A Koppel
arXiv preprint arXiv:2002.12475, 2020
202020
A class of parallel doubly stochastic algorithms for large-scale learning
A Mokhtari, A Koppel, A Ribeiro
arXiv preprint arXiv:1606.04991, 2016
202016
Asynchronous Decentralized Stochastic Optimization in Heterogeneous Networks
AS Bedi, A Koppel, K Rajawat
IEEE Trans. Signal Process (submitted)., 2017
19*2017
A variational approach to dual methods for constrained convex optimization
M Fazlyab, A Koppel, VM Preciado, A Ribeiro
2017 American Control Conference (ACC), 5269-5275, 2017
192017
Achieving zero constraint violation for constrained reinforcement learning via primal-dual approach
Q Bai, AS Bedi, M Agarwal, A Koppel, V Aggarwal
Proceedings of the AAAI Conference on Artificial Intelligence 36 (4), 3682-3689, 2022
182022
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