| 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 | 154 | 2015 |
| 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 | 132 | 2020 |
| 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 | 78 | 2016 |
| 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 | 72 | 2020 |
| 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 | 69 | 2015 |
| 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 | 58 | 2019 |
| Decentralized online learning with kernels A Koppel, S Paternain, C Richard, A Ribeiro IEEE Transactions on Signal Processing 66 (12), 3240-3255, 2018 | 54 | 2018 |
| 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 | 40 | 2015 |
| 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 | 37 | 2017 |
| Consistent online gaussian process regression without the sample complexity bottleneck A Koppel, H Pradhan, K Rajawat Statistics and Computing 31, 1-18, 2021 | 26 | 2021 |
| 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 | 25 | 2016 |
| 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 | 21 | 2018 |
| Cautious reinforcement learning via distributional risk in the dual domain J Zhang, AS Bedi, M Wang, A Koppel arXiv preprint arXiv:2002.12475, 2020 | 20 | 2020 |
| A class of parallel doubly stochastic algorithms for large-scale learning A Mokhtari, A Koppel, A Ribeiro arXiv preprint arXiv:1606.04991, 2016 | 20 | 2016 |
| 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 | 19 | 2017 |
| 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 | 18 | 2022 |
Alejandro RibeiroUniversity of PennsylvaniaVerified email at seas.upenn.edu
