Alec Koppel
Alec Koppel
Research Scientist, U.S. Army Research Laboratory
Verified email at mail.mil - 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
1052015
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
75*
Proximity without consensus in online multi-agent optimization
A Koppel, BM Sadler, A Ribeiro
Proc. Int. Conf. Accoustics Speech Signal Proces (submitted),, 2016
602016
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
442015
Global convergence of policy gradient methods to (almost) locally optimal policies
K Zhang, A Koppel, H Zhu, T Başar
arXiv preprint arXiv:1906.08383, 2019
38*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
372015
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
302017
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
26*2019
Decentralized online learning with kernels
A Koppel, S Paternain, C Richard, A Ribeiro
IEEE Transactions on Signal Processing 66 (12), 3240-3255, 2018
242018
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
202016
A class of parallel doubly stochastic algorithms for large-scale learning
A Mokhtari, A Koppel, A Ribeiro
arXiv preprint arXiv:1606.04991, 2016
192016
Doubly Random Parallel Stochastic Methods for Large Scale Learning
A Mokhtari, A Koppel, A Ribeiro
American Control Conference (submitted), 2016
182016
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 (submitted), 2017
15*2017
Prediction-correction methods for time-varying convex optimization
A Simonetto, A Koppel, A Mokhtari, G Leus, A Ribeiro
Proceedings of the Asilomar Conference on Signals, Systems, and Computers …, 2015
142015
Large-scale nonconvex stochastic optimization by doubly stochastic successive convex approximation
A Mokhtari, A Koppel, G Scutari, A Ribeiro
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
132017
Target Tracking with Dynamic Convex Optimization
A Koppel, A Simonetto, A Mokhtari, G Leus, A Ribeiro
Global Conference on Signal and Information Processing (GlobalSIP), 2015
132015
Asynchronous Decentralized Stochastic Optimization in Heterogeneous Networks
AS Bedi, A Koppel, K Rajawat
IEEE Trans. Signal Process (submitted)., 2017
12*2017
Consistent Online Gaussian Process Regression Without the Sample Complexity Bottleneck
A Koppel, H Pradhan, K Rajawat
arXiv:2004.11094, 2020
112020
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
112019
Beyond consensus and synchrony in online network optimization via saddle point method
AS Bedi, A Koppel, K Rajawat
arXiv preprint arXiv:1707.05816, 2017
9*2017
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