Alejandro Ribeiro

ORCID

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 526

Top Venues

CoRR

ICASSP

IEEE Trans. Signal Process.

CDC

Publications

Charilaos I. Kanatsoulis, Alejandro Ribeiro
Graph Neural Networks are More Powerful than We Think. ICASSP (2024)
Dongsheng Ding, Zhengyan Huan, Alejandro Ribeiro
Resilient Constrained Reinforcement Learning. AISTATS (2024)
Alejandro Parada-Mayorga, Alejandro Ribeiro
Sampling and Uniqueness Sets in Graphon Signal Processing. CoRR (2024)
Gabriel Egan, Mark Eisen, Alejandro Ribeiro, Santiago Segarra
A reply to Pervez Rizvi's letter. Digit. Scholarsh. Humanit. 39 (1) (2024)
Yigit Berkay Uslu, Roya Doostnejad, Alejandro Ribeiro, Navid Naderializadeh
Learning to Slice Wi-Fi Networks: A State-Augmented Primal-Dual Approach. CoRR (2024)
Harshat Kumar, Alejandro Parada-Mayorga, Alejandro Ribeiro
Lie Group Algebra Convolutional Filters. IEEE Trans. Signal Process. 72 (2024)
Miguel Calvo-Fullana, Santiago Paternain, Luiz F. O. Chamon, Alejandro Ribeiro
State Augmented Constrained Reinforcement Learning: Overcoming the Limitations of Learning With Rewards. IEEE Trans. Autom. Control. 69 (7) (2024)
Charilaos I. Kanatsoulis, Alejandro Ribeiro
Counting Graph Substructures with Graph Neural Networks. ICLR (2024)
Juan Elenter, Luiz F. O. Chamon, Alejandro Ribeiro
Near-Optimal Solutions of Constrained Learning Problems. ICLR (2024)
Xingran Chen, Navid Naderializadeh, Alejandro Ribeiro, Shirin Saeedi Bidokhti
Decentralized Learning Strategies for Estimation Error Minimization with Graph Neural Networks. CoRR (2024)
Claudio Battiloro, Zhiyang Wang, Hans Riess, Paolo Di Lorenzo, Alejandro Ribeiro
Tangent Bundle Convolutional Learning: From Manifolds to Cellular Sheaves and Back. IEEE Trans. Signal Process. 72 (2024)
Sourajit Das, Navid Naderializadeh, Alejandro Ribeiro
State-Augmented Information Routing In Communication Systems With Graph Neural Networks. ICASSP (2024)
Juan Cerviño, Md Asadullah Turja, Hesham Mostafa, Nageen Himayat, Alejandro Ribeiro
Distributed Training of Large Graph Neural Networks with Variable Communication Rates. CoRR (2024)
Saurabh Sihag, Gonzalo Mateos, Alejandro Ribeiro
Towards a Foundation Model for Brain Age Prediction using coVariance Neural Networks. CoRR (2024)
Zhiyang Wang, Luana Ruiz, Alejandro Ribeiro
Geometric Graph Filters and Neural Networks: Limit Properties and Discriminability Trade-Offs. IEEE Trans. Signal Process. 72 (2024)
Damian Owerko, Fernando Gama, Alejandro Ribeiro
Unsupervised Optimal Power Flow Using Graph Neural Networks. ICASSP (2024)
Juan Elenter, Luiz F. O. Chamon, Alejandro Ribeiro
Near-Optimal Solutions of Constrained Learning Problems. CoRR (2024)
Daniel Mox, Kashish Garg, Alejandro Ribeiro, Vijay Kumar
Opportunistic Communication in Robot Teams. ICRA (2024)
Alejandro Parada-Mayorga, Landon Butler, Alejandro Ribeiro
Non Commutative Convolutional Signal Models in Neural Networks: Stability to Small Deformations. ICASSP (2024)
Zhiyang Wang, Juan Cerviño, Alejandro Ribeiro
A Manifold Perspective on the Statistical Generalization of Graph Neural Networks. CoRR (2024)
Ignacio Hounie, Javier Porras-Valenzuela, Alejandro Ribeiro
Loss Shaping Constraints for Long-Term Time Series Forecasting. CoRR (2024)
Zhiyang Wang, Luana Ruiz, Alejandro Ribeiro
Stability to Deformations of Manifold Filters and Manifold Neural Networks. IEEE Trans. Signal Process. 72 (2024)
Saurav Agarwal, Ramya Muthukrishnan, Walker Gosrich, Alejandro Ribeiro, Vijay Kumar
LPAC: Learnable Perception-Action-Communication Loops with Applications to Coverage Control. CoRR (2024)
Claudio Battiloro, Paolo Di Lorenzo, Alejandro Ribeiro
Parametric Dictionary Learning for Topological Signal Representation. EUSIPCO (2023)
Juan Cerviño, Luiz F. O. Chamon, Benjamin David Haeffele, René Vidal, Alejandro Ribeiro
Learning Globally Smooth Functions on Manifolds. ICML (2023)
Shubhankar P. Patankar, Mathieu Ouellet, Juan Cerviño, Alejandro Ribeiro, Kieran A. Murphy, Dani S. Bassett
Intrinsically motivated graph exploration using network theories of human curiosity. CoRR (2023)
Ignacio Hounie, Luiz F. O. Chamon, Alejandro Ribeiro
Automatic Data Augmentation via Invariance-Constrained Learning. ICML (2023)
Dongsheng Ding, Chen-Yu Wei, Kaiqing Zhang, Alejandro Ribeiro
Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs. CoRR (2023)
Samar Hadou, Navid Naderializadeh, Alejandro Ribeiro
Stochastic Unrolled Federated Learning. CoRR (2023)
Samar Hadou, Navid Naderializadeh, Alejandro Ribeiro
Robust Stochastically-Descending Unrolled Networks. CoRR (2023)
Saurav Agarwal, Alejandro Ribeiro, Vijay Kumar
Asynchronous Perception-Action-Communication with Graph Neural Networks. CoRR (2023)
Damian Owerko, Charilaos I. Kanatsoulis, Jennifer Bondarchuk, Donald J. Bucci, Alejandro Ribeiro
Multi-Target Tracking with Transferable Convolutional Neural Networks. CAMSAP (2023)
Luiz F. O. Chamon, Santiago Paternain, Miguel Calvo-Fullana, Alejandro Ribeiro
Constrained Learning With Non-Convex Losses. IEEE Trans. Inf. Theory 69 (3) (2023)
Claudio Battiloro, Zhiyang Wang, Hans Riess, Paolo Di Lorenzo, Alejandro Ribeiro
Tangent Bundle Filters and Neural Networks: From Manifolds to Cellular Sheaves and Back. ICASSP (2023)
Zhiyang Wang, Luana Ruiz, Alejandro Ribeiro
Geometric Graph Filters and Neural Networks: Limit Properties and Discriminability Trade-offs. CoRR (2023)
Igor Spasojevic, Xu Liu, Alejandro Ribeiro, George J. Pappas, Vijay Kumar
Active Collaborative Localization in Heterogeneous Robot Teams. Robotics: Science and Systems (2023)
Shubhankar Prashant Patankar, Mathieu Ouellet, Juan Cerviño, Alejandro Ribeiro, Kieran A. Murphy, Danielle S. Bassett
Intrinsically Motivated Graph Exploration Using Network Theories of Human Curiosity. LoG (2023)
Miguel Calvo-Fullana, Mikhail Gerasimenko, Daniel Mox, Leopoldo Agorio, Mariana del Castillo, Vijay Kumar, Alejandro Ribeiro, Juan Andrés Bazerque
A Networked Multi-Agent System for Mobile Wireless Infrastructure on Demand. CoRR (2023)
Ignacio Hounie, Alejandro Ribeiro, Luiz F. O. Chamon
Resilient Constrained Learning. NeurIPS (2023)
Saurabh Sihag, Gonzalo Mateos, Corey T. McMillan, Alejandro Ribeiro
Explainable Brain Age Prediction using coVariance Neural Networks. CoRR (2023)
Max Wasserman, Saurabh Sihag, Gonzalo Mateos, Alejandro Ribeiro
Learning Graph Structure from Convolutional Mixtures. Trans. Mach. Learn. Res. 2023 (2023)
Saurabh Sihag, Gonzalo Mateos, Corey McMillan, Alejandro Ribeiro
Explainable Brain Age Prediction using coVariance Neural Networks. NeurIPS (2023)
Igor Spasojevic, Xu Liu, Ankit Prabhu, Alejandro Ribeiro, George J. Pappas, Vijay Kumar
Robust Localization of Aerial Vehicles via Active Control of Identical Ground Vehicles. IROS (2023)
Hesham Mostafa, Adam Grabowski, Md Asadullah Turja, Juan Cerviño, Alejandro Ribeiro, Nageen Himayat
FastSample: Accelerating Distributed Graph Neural Network Training for Billion-Scale Graphs. CoRR (2023)
Claudio Battiloro, Zhiyang Wang, Hans Riess, Paolo Di Lorenzo, Alejandro Ribeiro
Tangent Bundle Convolutional Learning: from Manifolds to Cellular Sheaves and Back. CoRR (2023)
Ignacio Hounie, Alejandro Ribeiro, Luiz F. O. Chamon
Resilient Constrained Learning. CoRR (2023)
Dongsheng Ding, Zhengyan Huan, Alejandro Ribeiro
Resilient Constrained Reinforcement Learning. CoRR (2023)
Igor Spasojevic, Xu Liu, Alejandro Ribeiro, George J. Pappas, Vijay Kumar
Active Collaborative Localization in Heterogeneous Robot Teams. CoRR (2023)
Harshat Kumar, Alec Koppel, Alejandro Ribeiro
On the sample complexity of actor-critic method for reinforcement learning with function approximation. Mach. Learn. 112 (7) (2023)
Juan Cerviño, Luana Ruiz, Alejandro Ribeiro
Learning by Transference: Training Graph Neural Networks on Growing Graphs. IEEE Trans. Signal Process. 71 (2023)
Juan Cerviño, Juan Andrés Bazerque, Miguel Calvo-Fullana, Alejandro Ribeiro
Multi-Task Bias-Variance Trade-Off Through Functional Constraints. ICASSP (2023)
Damian Owerko, Charilaos I. Kanatsoulis, Alejandro Ribeiro
Solving Large-Scale Spatial Problems with Convolutional Neural Networks. ACSSC (2023)
Ignacio Boero, Igor Spasojevic, Mariana del Castillo, George J. Pappas, Vijay Kumar, Alejandro Ribeiro
Navigation with Shadow Prices to Optimize Multi-Commodity Flow Rates. CDC (2023)
Alejandro Parada-Mayorga, Zhiyang Wang, Fernando Gama, Alejandro Ribeiro
Stability of Aggregation Graph Neural Networks. IEEE Trans. Signal Inf. Process. over Networks 9 (2023)
Elijah S. Lee, Lifeng Zhou, Alejandro Ribeiro, Vijay Kumar
Graph Neural Networks for Decentralized Multi-Agent Perimeter Defense. CoRR (2023)
Zhiyang Wang, Luana Ruiz, Alejandro Ribeiro
Convergence of Graph Neural Networks on Relatively Sparse Graphs. ACSSC (2023)
Gabriel Egan, Mark Eisen, Alejandro Ribeiro, Santiago Segarra
"I would I had that corporal soundness": Pervez Rizvi's Analysis of the Word Adjacency Network Method of Authorship Attribution. Digit. Scholarsh. Humanit. 38 (4) (2023)
Dongsheng Ding, Chen-Yu Wei, Kaiqing Zhang, Alejandro Ribeiro
Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs. NeurIPS (2023)
Ignacio Boero, Igor Spasojevic, Mariana del Castillo, George J. Pappas, Vijay Kumar, Alejandro Ribeiro
Navigation with shadow prices to optimize multi-commodity flow rates. CoRR (2023)
Jiashu He, Charilaos I. Kanatsoulis, Alejandro Ribeiro
Network Alignment with Transferable Graph Autoencoders. CoRR (2023)
Saurabh Sihag, Gonzalo Mateos, Corey T. McMillan, Alejandro Ribeiro
Transferability of coVariance Neural Networks and Application to Interpretable Brain Age Prediction using Anatomical Features. CoRR (2023)
Navid Naderializadeh, Mark Eisen, Alejandro Ribeiro
Learning Resilient Radio Resource Management Policies With Graph Neural Networks. IEEE Trans. Signal Process. 71 (2023)
Ignacio Hounie, Juan Elenter, Alejandro Ribeiro
Neural Networks with Quantization Constraints. ICASSP (2023)
Luana Ruiz, Luiz F. O. Chamon, Alejandro Ribeiro
Transferability Properties of Graph Neural Networks. IEEE Trans. Signal Process. 71 (2023)
Harshat Kumar, Alejandro Parada-Mayorga, Alejandro Ribeiro
Algebraic Convolutional Filters on Lie Group Algebras. ICASSP (2023)
Samar Hadou, Charilaos I. Kanatsoulis, Alejandro Ribeiro
Space-Time Graph Neural Networks with Stochastic Graph Perturbations. ICASSP (2023)
Landon Butler, Alejandro Parada-Mayorga, Alejandro Ribeiro
Convolutional Learning on Multigraphs. IEEE Trans. Signal Process. 71 (2023)
Alejandro Parada-Mayorga, Zhiyang Wang, Alejandro Ribeiro
Graphon Pooling for Reducing Dimensionality of Signals and Convolutional Operators on Graphs. IEEE Trans. Signal Process. 71 (2023)
Santiago Paternain, Miguel Calvo-Fullana, Luiz F. O. Chamon, Alejandro Ribeiro
Safe Policies for Reinforcement Learning via Primal-Dual Methods. IEEE Trans. Autom. Control. 68 (3) (2023)
Juan Cerviño, Luana Ruiz, Alejandro Ribeiro
Training Graph Neural Networks on Growing Stochastic Graphs. ICASSP (2023)
Damian Owerko, Charilaos I. Kanatsoulis, Jennifer Bondarchuk, Donald J. Bucci Jr., Alejandro Ribeiro
Transferability of Convolutional Neural Networks in Stationary Learning Tasks. CoRR (2023)
Shervin Khalafi, Saurabh Sihag, Alejandro Ribeiro
Neural Tangent Kernels Motivate Graph Neural Networks with Cross-Covariance Graphs. CoRR (2023)
Alejandro Parada-Mayorga, Landon Butler, Alejandro Ribeiro
Non Commutative Convolutional Signal Models in Neural Networks: Stability to Small Deformations. CoRR (2023)
Alejandro Parada-Mayorga, Landon Butler, Alejandro Ribeiro
Convolutional Filters and Neural Networks With Noncommutative Algebras. IEEE Trans. Signal Process. 71 (2023)
Mikhail Hayhoe, Hans Riess, Michael M. Zavlanos, Victor M. Preciado, Alejandro Ribeiro
Transferable Hypergraph Neural Networks via Spectral Similarity. LoG (2023)
Saurabh Sihag, Gonzalo Mateos, Corey McMillan, Alejandro Ribeiro
Predicting Brain Age Using Transferable Covariance Neural Networks. ICASSP (2023)
Zhiyang Wang, Luana Ruiz, Alejandro Ribeiro
Convolutional Filtering on Sampled Manifolds. ICASSP (2023)
Igor Spasojevic, Xu Liu, Ankit Prabhu, Alejandro Ribeiro, George J. Pappas, Vijay Kumar
Robust Localization of Aerial Vehicles via Active Control of Identical Ground Vehicles. CoRR (2023)
Sourajit Das, Navid Naderializadeh, Alejandro Ribeiro
Learning State-Augmented Policies for Information Routing in Communication Networks. CoRR (2023)
Landon Butler, Alejandro Parada-Mayorga, Alejandro Ribeiro
Learning with Multigraph Convolutional Filters. ICASSP (2023)
Juan Elenter, Navid Naderializadeh, Tara Javidi, Alejandro Ribeiro
Primal-Dual Continual Learning: Stability and Plasticity through Lagrange Multipliers. CoRR (2023)
Luiz F. O. Chamon, Alexandre Amice, Alejandro Ribeiro
Approximately Supermodular Scheduling Subject to Matroid Constraints. IEEE Trans. Autom. Control. 67 (3) (2022)
Yigit Berkay Uslu, Navid Naderializadeh, Mark Eisen, Alejandro Ribeiro
A State-Augmented Approach for Learning Optimal Resource Management Decisions in Wireless Networks. CoRR (2022)
Zhan Gao, Fernando Gama, Alejandro Ribeiro
Spherical convolutional neural networks: Stability to perturbations in SO(3). Signal Process. 196 (2022)
Zhan Gao, Mark Eisen, Alejandro Ribeiro
Resource Allocation via Model-Free Deep Learning in Free Space Optical Communications. IEEE Trans. Commun. 70 (2) (2022)
Elvin Isufi, Fernando Gama, Alejandro Ribeiro
EdgeNets: Edge Varying Graph Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. 44 (11) (2022)
Zhan Gao, Alec Koppel, Alejandro Ribeiro
Balancing Rates and Variance via Adaptive Batch-Size for Stochastic Optimization Problems. IEEE Trans. Signal Process. 70 (2022)
Zhiyang Wang, Luana Ruiz, Mark Eisen, Alejandro Ribeiro
Stable and Transferable Wireless Resource Allocation Policies Via Manifold Neural Networks. ICASSP (2022)
Zebang Shen, Zhenfu Wang, Satyen Kale, Alejandro Ribeiro, Amin Karbasi, Hamed Hassani
Self-Consistency of the Fokker-Planck Equation. CoRR (2022)
Samar Hadou, Charilaos I. Kanatsoulis, Alejandro Ribeiro
Space-Time Graph Neural Networks with Stochastic Graph Perturbations. CoRR (2022)
Zhan Gao, Fernando Gama, Alejandro Ribeiro
Wide and Deep Graph Neural Network With Distributed Online Learning. IEEE Trans. Signal Process. 70 (2022)
Saurabh Sihag, Gonzalo Mateos, Corey McMillan, Alejandro Ribeiro
Predicting Brain Age using Transferable coVariance Neural Networks. CoRR (2022)
Landon Butler, Alejandro Parada-Mayorga, Alejandro Ribeiro
Convolutional Learning on Multigraphs. CoRR (2022)
Walker Gosrich, Siddharth Mayya, Rebecca Li, James Paulos, Mark Yim, Alejandro Ribeiro, Vijay Kumar
Coverage Control in Multi-Robot Systems via Graph Neural Networks. ICRA (2022)
Zhiyang Wang, Luana Ruiz, Alejandro Ribeiro
Convolutional Neural Networks on Manifolds: From Graphs and Back. CoRR (2022)
Zhiyang Wang, Luana Ruiz, Alejandro Ribeiro
Convolutional Neural Networks on Manifolds: From Graphs and Back. IEEECONF (2022)
Lifeng Zhou, Vishnu D. Sharma, Qingbiao Li, Amanda Prorok, Alejandro Ribeiro, Pratap Tokekar, Vijay Kumar
Graph Neural Networks for Decentralized Multi-Robot Target Tracking. SSRR (2022)
Zebang Shen, Zhenfu Wang, Satyen Kale, Alejandro Ribeiro, Amin Karbasi, Hamed Hassani
Self-Consistency of the Fokker Planck Equation. COLT (2022)
Fernando Gama, Qingbiao Li, Ekaterina I. Tolstaya, Amanda Prorok, Alejandro Ribeiro
Synthesizing Decentralized Controllers With Graph Neural Networks and Imitation Learning. IEEE Trans. Signal Process. 70 (2022)
Zhiyang Wang, Mark Eisen, Alejandro Ribeiro
Learning Decentralized Wireless Resource Allocations With Graph Neural Networks. IEEE Trans. Signal Process. 70 (2022)

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Publication Activity (10 Years)

Top Topics

Top Venues

Alejandro Ribeiro