Juan Andrés Bazerque

Orcid: 0000-0001-9950-1208

According to our database1, Juan Andrés Bazerque authored at least 42 papers between 2008 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
A Networked Multiagent System for Mobile Wireless Infrastructure on Demand.
IEEE Trans. Robotics, 2024

Convolutional Filtering with RKHS Algebras.
CoRR, 2024

Multi-agent assignment via state augmented reinforcement learning.
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, 2024

Combined learning and optimal power flow for storage dispatch in grids with renewables.
Proceedings of the IEEE Power & Energy Society Innovative Smart Grid Technologies Conference, 2024

2023
Learning to Act Safely With Limited Exposure and Almost Sure Certainty.
IEEE Trans. Autom. Control., May, 2023

A Networked Multi-Agent System for Mobile Wireless Infrastructure on Demand.
CoRR, 2023

Multi-Task Bias-Variance Trade-Off Through Functional Constraints.
Proceedings of the IEEE International Conference on Acoustics, 2023

Learning Safety Critics via a Non-Contractive Binary Bellman Operator.
Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023

2022
Policy Gradient for Continuing Tasks in Discounted Markov Decision Processes.
IEEE Trans. Autom. Control., 2022

Reinforcement Learning with Almost Sure Constraints.
Proceedings of the Learning for Dynamics and Control Conference, 2022

2021
Multi-Task Reinforcement Learning in Reproducing Kernel Hilbert Spaces via Cross-Learning.
IEEE Trans. Signal Process., 2021

Stochastic Policy Gradient Ascent in Reproducing Kernel Hilbert Spaces.
IEEE Trans. Autom. Control., 2021

Multi-task Supervised Learning via Cross-learning.
Proceedings of the 29th European Signal Processing Conference, 2021

Model-free safe policy learning via hard action barrier functions.
Proceedings of the 55th Annual Conference on Information Sciences and Systems, 2021

Learning to be safe, in finite time.
Proceedings of the 2021 American Control Conference, 2021

2020
Assured RL: Reinforcement Learning with Almost Sure Constraints.
CoRR, 2020

Policy Gradient for Continuing Tasks in Non-stationary Markov Decision Processes.
CoRR, 2020

Quadratic approximate dynamic programming for scheduling water resources: a case study.
CoRR, 2020

Learning the operation of energy storage systems from real trajectories of demand and renewables.
Proceedings of the IEEE Power & Energy Society Innovative Smart Grid Technologies Conference, 2020

2019
Demand Response and Ancillary Services for Supercomputing and Datacenters.
Proceedings of the Supercomputing, 2019

Policy Improvement Directions for Reinforcement Learning in Reproducing Kernel Hilbert Spaces.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Meta-Learning through Coupled Optimization in Reproducing Kernel Hilbert Spaces.
Proceedings of the 2019 American Control Conference, 2019

2018
Stochastic Optimization of Power Systems with Risk Constraints And Sparsely Distributed Storage.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Learning Policies for Markov Decision Processes in Continuous Spaces.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018

2017
Control of networked systems in the graph-frequency domain.
Proceedings of the 51st Asilomar Conference on Signals, Systems, and Computers, 2017

2013
Rank Regularization and Bayesian Inference for Tensor Completion and Extrapolation.
IEEE Trans. Signal Process., 2013

Nonparametric Basis Pursuit via Sparse Kernel-Based Learning: A Unifying View with Advances in Blind Methods.
IEEE Signal Process. Mag., 2013

Inference of Gene Regulatory Networks with Sparse Structural Equation Models Exploiting Genetic Perturbations.
PLoS Comput. Biol., 2013

Nonparametric Basis Pursuit via Sparse Kernel-based Learning
CoRR, 2013

Inference of Poisson count processes using low-rank tensor data.
Proceedings of the IEEE International Conference on Acoustics, 2013

Identifiability of sparse structural equation models for directed and cyclic networks.
Proceedings of the IEEE Global Conference on Signal and Information Processing, 2013

2012
Group sparse Lasso for cognitive network sensing robust to model uncertainties and outliers.
Phys. Commun., 2012

Nonparametric low-rank tensor imputation.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2012

2011
Group-Lasso on Splines for Spectrum Cartography.
IEEE Trans. Signal Process., 2011

Basis pursuit for spectrum cartography.
Proceedings of the IEEE International Conference on Acoustics, 2011

Gene network inference via sparse structural equation modeling with genetic perturbations.
Proceedings of the 2011 IEEE International Workshop on Genomic Signal Processing and Statistics, 2011

2010
Distributed sparse linear regression.
IEEE Trans. Signal Process., 2010

Distributed spectrum sensing for cognitive radio networks by exploiting sparsity.
IEEE Trans. Signal Process., 2010

Online adaptive estimation of sparse signals: where RLS meets the l1-norm.
IEEE Trans. Signal Process., 2010

Distributed Lasso for in-network linear regression.
Proceedings of the IEEE International Conference on Acoustics, 2010

2008
Distributed Scheduling and Resource Allocation for Cognitive OFDMA Radios.
Mob. Networks Appl., 2008

Distributed spectrum sensing for cognitive radios by exploiting sparsity.
Proceedings of the 42nd Asilomar Conference on Signals, Systems and Computers, 2008


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