Distributed spectrum sensing for cognitive radios by exploiting sparsity. - Juan Andrés Bazerque; Georgios B. Giannakis (ACSCC, 2008)

Distributed Scheduling and Resource Allocation for Cognitive OFDMA Radios. - Juan Andrés Bazerque; Georgios B. Giannakis (Mob. Networks Appl., 2008)

Distributed Lasso for in-network linear regression. - Juan Andrés Bazerque; Gonzalo Mateos; Georgios B. Giannakis (ICASSP, 2010)

Online adaptive estimation of sparse signals: where RLS meets the l1-norm. - Daniele Angelosante; Juan Andrés Bazerque; Georgios B. Giannakis (IEEE Trans. Signal Process., 2010)

Distributed spectrum sensing for cognitive radio networks by exploiting sparsity. - Juan Andrés Bazerque; Georgios B. Giannakis (IEEE Trans. Signal Process., 2010)

Distributed sparse linear regression. - Gonzalo Mateos; Juan Andrés Bazerque; Georgios B. Giannakis (IEEE Trans. Signal Process., 2010)

Gene network inference via sparse structural equation modeling with genetic perturbations. - Xiaodong Cai; Juan Andrés Bazerque; Georgios B. Giannakis (GENSiPS, 2011)

Basis pursuit for spectrum cartography. - Juan Andrés Bazerque; Gonzalo Mateos; Georgios B. Giannakis (ICASSP, 2011)

Group-Lasso on Splines for Spectrum Cartography. - Juan Andrés Bazerque; Gonzalo Mateos; Georgios B. Giannakis (IEEE Trans. Signal Process., 2011)

Nonparametric low-rank tensor imputation. - Juan Andrés Bazerque; Gonzalo Mateos; Georgios B. Giannakis (SSP, 2012)

Group sparse Lasso for cognitive network sensing robust to model uncertainties and outliers. - Emiliano Dall'Anese; Juan Andrés Bazerque; Georgios B. Giannakis (Phys. Commun., 2012)

Identifiability of sparse structural equation models for directed and cyclic networks. - Juan Andrés Bazerque; Brian Baingana; Georgios B. Giannakis (GlobalSIP, 2013)

Inference of Poisson count processes using low-rank tensor data. - Juan Andrés Bazerque; Gonzalo Mateos; Georgios B. Giannakis (ICASSP, 2013)

Nonparametric Basis Pursuit via Sparse Kernel-based Learning - Juan Andrés Bazerque; Georgios B. Giannakis (CoRR, 2013)

Inference of Gene Regulatory Networks with Sparse Structural Equation Models Exploiting Genetic Perturbations. - Xiaodong Cai; Juan Andrés Bazerque; Georgios B. Giannakis (PLoS Comput. Biol., 2013)

Nonparametric Basis Pursuit via Sparse Kernel-Based Learning: A Unifying View with Advances in Blind Methods. - Juan Andrés Bazerque; Georgios B. Giannakis (IEEE Signal Process. Mag., 2013)

Rank Regularization and Bayesian Inference for Tensor Completion and Extrapolation. - Juan Andrés Bazerque; Gonzalo Mateos; Georgios B. Giannakis (IEEE Trans. Signal Process., 2013)

Control of networked systems in the graph-frequency domain. - Juan Andrés Bazerque; Pablo Monzón (ACSSC, 2017)

Learning Policies for Markov Decision Processes in Continuous Spaces. - Santiago Paternain; Juan Andrés Bazerque; Austin Small; Alejandro Ribeiro (CDC, 2018)

Stochastic Optimization of Power Systems with Risk Constraints And Sparsely Distributed Storage. - Juan Andrés Bazerque (ICASSP, 2018)

Meta-Learning through Coupled Optimization in Reproducing Kernel Hilbert Spaces. - Juan Cerviño; Juan Andrés Bazerque; Miguel Calvo-Fullana; Alejandro Ribeiro (ACC, 2019)

Policy Improvement Directions for Reinforcement Learning in Reproducing Kernel Hilbert Spaces. - Santiago Paternain; Juan Andrés Bazerque; Austin Small; Alejandro Ribeiro (CDC, 2019)

Demand Response and Ancillary Services for Supercomputing and Datacenters. - Sergio Nesmachnow; Santiago Iturriaga; Jonathan Muraña; Sebastian Montes de Oca; Gonzalo Belcredi; Pablo Monzón; Pablo Belzarena; Juan Andrés Bazerque (ISUM, 2019)

Learning the operation of energy storage systems from real trajectories of demand and renewables. - Agustin Castellano; Juan Andrés Bazerque (ISGT, 2020)

Quadratic approximate dynamic programming for scheduling water resources: a case study. - Agustin Castellano; Camila Martínez; Pablo Monzón; Juan Andrés Bazerque; Andrés Ferragut; Fernando Paganini (CoRR, 2020)

Policy Gradient for Continuing Tasks in Non-stationary Markov Decision Processes. - Santiago Paternain; Juan Andrés Bazerque; Alejandro Ribeiro (CoRR, 2020)

Assured RL: Reinforcement Learning with Almost Sure Constraints. - Agustin Castellano; Juan Andrés Bazerque; Enrique Mallada (CoRR, 2020)

Learning to be safe, in finite time. - Agustin Castellano; Juan Andrés Bazerque; Enrique Mallada (ACC, 2021)

Model-free safe policy learning via hard action barrier functions. - Agustin Castellano; Juan Andrés Bazerque; Enrique Mallada (CISS, 2021)

Multi-task Supervised Learning via Cross-learning. - Juan Cerviño; Juan Andrés Bazerque; Miguel Calvo-Fullana; Alejandro Ribeiro (EUSIPCO, 2021)

Stochastic Policy Gradient Ascent in Reproducing Kernel Hilbert Spaces. - Santiago Paternain; Juan Andrés Bazerque; Austin Small; Alejandro Ribeiro (IEEE Trans. Autom. Control., 2021)

Multi-Task Reinforcement Learning in Reproducing Kernel Hilbert Spaces via Cross-Learning. - Juan Cerviño; Juan Andrés Bazerque; Miguel Calvo-Fullana; Alejandro Ribeiro (IEEE Trans. Signal Process., 2021)

Reinforcement Learning with Almost Sure Constraints. - Agustin Castellano; Hancheng Min; Enrique Mallada; Juan Andrés Bazerque (L4DC, 2022)

Policy Gradient for Continuing Tasks in Discounted Markov Decision Processes. - Santiago Paternain; Juan Andrés Bazerque; Alejandro Ribeiro (IEEE Trans. Autom. Control., 2022)

Learning Safety Critics via a Non-Contractive Binary Bellman Operator. - Agustin Castellano; Hancheng Min; Juan Andrés Bazerque; Enrique Mallada (ACSSC, 2023)

Multi-Task Bias-Variance Trade-Off Through Functional Constraints. - Juan Cerviño; Juan Andrés Bazerque; Miguel Calvo-Fullana; Alejandro Ribeiro (ICASSP, 2023)

A Networked Multi-Agent System for Mobile Wireless Infrastructure on Demand. - Miguel Calvo-Fullana; Mikhail Gerasimenko; Daniel Mox; Leopoldo Agorio; Mariana del Castillo; Vijay Kumar 001; Alejandro Ribeiro; Juan Andrés Bazerque (CoRR, 2023)

Learning to Act Safely With Limited Exposure and Almost Sure Certainty. - Agustin Castellano; Hancheng Min; Juan Andrés Bazerque; Enrique Mallada (IEEE Trans. Autom. Control., 2023)

A Tensor Low-Rank Approximation for Value Functions in Multi-Task Reinforcement Learning. - Sergio Rozada; Santiago Paternain; Juan Andrés Bazerque; Antonio G. Marques (IEEECONF, 2024)

Combined learning and optimal power flow for storage dispatch in grids with renewables. - Rodrigo Porteiro; Fernando Paganini; Juan Andrés Bazerque (ISGT, 2024)

Multi-agent assignment via state augmented reinforcement learning. - Leopoldo Agorio; Sean Van Alen; Miguel Calvo-Fullana; Santiago Paternain; Juan Andrés Bazerque (L4DC, 2024)

A Networked Multiagent System for Mobile Wireless Infrastructure on Demand. - Miguel Calvo-Fullana; Mikhail Gerasimenko; Daniel Mox; Leopoldo Agorio; Mariana del Castillo; Vijay Kumar 001; Alejandro Ribeiro; Juan Andrés Bazerque (IEEE Trans. Robotics, 2024)

Convolutional Filtering With RKHS Algebras. - Alejandro Parada-Mayorga; Leopoldo Agorio; Alejandro Ribeiro; Juan Andrés Bazerque (IEEE Trans. Signal Process., 2025)

Cooperative Multi-Agent Assignment over Stochastic Graphs via Constrained Reinforcement Learning. - Leopoldo Agorio; Sean Van Alen; Santiago Paternain; Miguel Calvo-Fullana; Juan Andrés Bazerque (CoRR, 2025)