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- Alec Koppel, Felicia Y. Jakubiec, Alejandro R. Ribeiro
- IEEE Transactions on Signal Processing
- 2014

An algorithm to learn optimal actions in convex distributed online problems is developed. Learning is online because cost functions are revealed sequentially and distributed because they are revealedâ€¦ (More)

- Alec Koppel, Brian M. Sadler, Alejandro R. Ribeiro
- IEEE Transactions on Signal Processing
- 2016

We consider stochastic optimization problems in multiagent settings, where a network of agents aims to learn parameters that are optimal in terms of a global convex objective, while giving preferenceâ€¦ (More)

- Alec Koppel, Garrett Warnell, Ethan Stump, Alejandro R. Ribeiro
- IEEE Transactions on Signal and Informationâ€¦
- 2015

We consider discriminative dictionary learning in a distributed online setting, where a network of agents aims to learn, from sequential observations, statistical model parameters jointly withâ€¦ (More)

- Aryan Mokhtari, Alec Koppel, Alejandro R. Ribeiro
- 2016 American Control Conference (ACC)
- 2016

We consider learning problems over training sets in which both, the number of training examples and the dimension of the feature vectors, are large. To solve these problems we propose the randomâ€¦ (More)

- Aryan Mokhtari, Alec Koppel, Gesualdo Scutari, Alejandro R. Ribeiro
- 2017 IEEE International Conference on Acousticsâ€¦
- 2017

We consider supervised learning problems over training sets in which both the number of training examples and the dimension of the feature vectors are large. We focus on the case where the lossâ€¦ (More)

- Andrea Simonetto, Aryan Mokhtari, Alec Koppel, Geert Leus, Alejandro R. Ribeiro
- IEEE Transactions on Signal Processing
- 2016

This paper considers unconstrained convex optimization problems with time-varying objective functions. We propose algorithms with a discrete time-sampling scheme to find and track the solutionâ€¦ (More)

- Andrea Simonetto, Alec Koppel, Aryan Mokhtari, G. Leus, Alejandro R. Ribeiro
- IEEE Transactions on Automatic Control
- 2017

We develop algorithms that find and track the optimal solution trajectory of time-varying convex optimization problems that consist of local and network-related objectives. The algorithms are derivedâ€¦ (More)

- Andrea Simonetto, Alec Koppel, Aryan Mokhtari, Geert Leus, Alejandro R. Ribeiro
- 2015 49th Asilomar Conference on Signals, Systemsâ€¦
- 2015

We consider unconstrained convex optimization problems with objective functions that vary continuously in time. We propose algorithms with a discrete time-sampling scheme to find and track theâ€¦ (More)

- Alec Koppel, Jonathan Fink, Garrett Warnell, Ethan Stump, Alejandro R. Ribeiro
- 2016 IEEE/RSJ International Conference onâ€¦
- 2016

In pursuit of increasing the operational tempo of a ground robotics platform in unknown domains, we consider the problem of predicting the distribution of structural state-estimation error due toâ€¦ (More)

- Aryan Mokhtari, Alec Koppel, Alejandro R. Ribeiro
- ArXiv
- 2016

We consider learning problems over training sets in which both, the number of training examples and the dimension of the feature vectors, are large. To solve these problems we propose the randomâ€¦ (More)