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ORCIDAlejandro Ribeiro
Person information
- affiliation: University of Pennsylvania, Department of Electrical and Systems Engineering, Philadelphia, PA, USA
- affiliation (PhD 2007): University of Minnesota, Department of Electrical and Computer Engineering, Minneapolis, MN, USA
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2020 – today
- 2025
[j157]Sourajit Das, Navid Naderializadeh, Alejandro Ribeiro:
Learning State-Augmented Policies for Information Routing in Communication Networks. IEEE Trans. Signal Process. 73: 204-218 (2025)- 2024
- [j156]Gabriel Egan, Mark Eisen, Alejandro Ribeiro, Santiago Segarra:
A reply to Pervez Rizvi's letter. Digit. Scholarsh. Humanit. 39(1): 3-4 (2024) - [j155]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): 4275-4290 (2024) - [j154]Miguel Calvo-Fullana, Mikhail Gerasimenko, Daniel Mox, Leopoldo Agorio, Mariana del Castillo, Vijay Kumar, Alejandro Ribeiro, Juan Andrés Bazerque:
A Networked Multiagent System for Mobile Wireless Infrastructure on Demand. IEEE Trans. Robotics 40: 4598-4614 (2024) - [j153]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: 1892-1909 (2024) - [j152]Zhiyang Wang, Luana Ruiz, Alejandro Ribeiro:
Stability to Deformations of Manifold Filters and Manifold Neural Networks. IEEE Trans. Signal Process. 72: 2130-2146 (2024) - [j151]Zhiyang Wang, Luana Ruiz, Alejandro Ribeiro:
Geometric Graph Filters and Neural Networks: Limit Properties and Discriminability Trade-Offs. IEEE Trans. Signal Process. 72: 2244-2259 (2024) - [j150]Harshat Kumar, Alejandro Parada-Mayorga, Alejandro Ribeiro:
Lie Group Algebra Convolutional Filters. IEEE Trans. Signal Process. 72: 2842-2857 (2024) - [j149]Samar Hadou, Navid Naderializadeh, Alejandro Ribeiro:
Robust Stochastically-Descending Unrolled Networks. IEEE Trans. Signal Process. 72: 5484-5499 (2024) - [c313]Dongsheng Ding, Zhengyan Huan, Alejandro Ribeiro:
Resilient Constrained Reinforcement Learning. AISTATS 2024: 3412-3420 - [c312]Mariana del Castillo, Alejandro Ribeiro, Federico Larroca:
EGNN-based Topology Control in Wireless Mobile Infrastructure on Demand with Shared Access Restrictions. GNNet@CoNEXT 2024: 46-52 - [c311]Damian Owerko, Fernando Gama, Alejandro Ribeiro:
Unsupervised Optimal Power Flow Using Graph Neural Networks. ICASSP 2024: 6885-6889 - [c310]Alejandro Parada-Mayorga, Landon Butler, Alejandro Ribeiro:
Non Commutative Convolutional Signal Models in Neural Networks: Stability to Small Deformations. ICASSP 2024: 7305-7309 - [c309]Charilaos I. Kanatsoulis, Alejandro Ribeiro:
Graph Neural Networks are More Powerful than We Think. ICASSP 2024: 7550-7554 - [c308]Sourajit Das, Navid Naderializadeh, Alejandro Ribeiro:
State-Augmented Information Routing In Communication Systems With Graph Neural Networks. ICASSP 2024: 9181-9185 - [c307]Juan Elenter, Luiz F. O. Chamon, Alejandro Ribeiro:
Near-Optimal Solutions of Constrained Learning Problems. ICLR 2024 - [c306]Charilaos I. Kanatsoulis, Alejandro Ribeiro:
Counting Graph Substructures with Graph Neural Networks. ICLR 2024 - [c305]Ignacio Hounie, Javier Porras-Valenzuela, Alejandro Ribeiro:
Loss Shaping Constraints for Long-Term Time Series Forecasting. ICML 2024 - [c304]Shervin Khalafi, Saurabh Sihag, Alejandro Ribeiro:
Neural Tangent Kernels Motivate Cross-Covariance Graphs in Neural Networks. ICML 2024 - [c303]Daniel Mox, Kashish Garg, Alejandro Ribeiro, Vijay Kumar:
Opportunistic Communication in Robot Teams. ICRA 2024: 12090-12096 - [i228]Saurav Agarwal, Ramya Muthukrishnan, Walker Gosrich, Vijay Kumar, Alejandro Ribeiro:
LPAC: Learnable Perception-Action-Communication Loops with Applications to Coverage Control. CoRR abs/2401.04855 (2024) - [i227]Alejandro Parada-Mayorga, Alejandro Ribeiro:
Sampling and Uniqueness Sets in Graphon Signal Processing. CoRR abs/2401.06279 (2024) - [i226]Saurabh Sihag, Gonzalo Mateos, Alejandro Ribeiro:
Towards a Foundation Model for Brain Age Prediction using coVariance Neural Networks. CoRR abs/2402.07684 (2024) - [i225]Ignacio Hounie, Javier Porras-Valenzuela, Alejandro Ribeiro:
Loss Shaping Constraints for Long-Term Time Series Forecasting. CoRR abs/2402.09373 (2024) - [i224]Juan Elenter, Luiz F. O. Chamon, Alejandro Ribeiro:
Near-Optimal Solutions of Constrained Learning Problems. CoRR abs/2403.11844 (2024) - [i223]Xingran Chen, Navid Naderializadeh, Alejandro Ribeiro, Shirin Saeedi Bidokhti:
Decentralized Learning Strategies for Estimation Error Minimization with Graph Neural Networks. CoRR abs/2404.03227 (2024) - [i222]Yigit Berkay Uslu, Roya Doostnejad, Alejandro Ribeiro, Navid Naderializadeh:
Learning to Slice Wi-Fi Networks: A State-Augmented Primal-Dual Approach. CoRR abs/2405.05748 (2024) - [i221]Zhiyang Wang, Juan Cerviño, Alejandro Ribeiro:
A Manifold Perspective on the Statistical Generalization of Graph Neural Networks. CoRR abs/2406.05225 (2024) - [i220]Juan Cerviño, Md Asadullah Turja, Hesham Mostafa, Nageen Himayat, Alejandro Ribeiro:
Distributed Training of Large Graph Neural Networks with Variable Communication Rates. CoRR abs/2406.17611 (2024) - [i219]Sergio Rozada, Dongsheng Ding, Antonio G. Marques, Alejandro Ribeiro:
Deterministic Policy Gradient Primal-Dual Methods for Continuous-Space Constrained MDPs. CoRR abs/2408.10015 (2024) - [i218]Zhiyang Wang, Juan Cerviño, Alejandro Ribeiro:
Generalization of Graph Neural Networks is Robust to Model Mismatch. CoRR abs/2408.13878 (2024) - [i217]Shervin Khalafi, Dongsheng Ding, Alejandro Ribeiro:
Constrained Diffusion Models via Dual Training. CoRR abs/2408.15094 (2024) - [i216]Zhiyang Wang, Juan Cerviño, Alejandro Ribeiro:
Generalization of Geometric Graph Neural Networks. CoRR abs/2409.05191 (2024) - [i215]Juan Cerviño, Saurav Agarwal, Vijay Kumar, Alejandro Ribeiro:
Constrained Learning for Decentralized Multi-Objective Coverage Control. CoRR abs/2409.11311 (2024) - [i214]Shreyas Muthusamy, Damian Owerko, Charilaos I. Kanatsoulis, Saurav Agarwal, Alejandro Ribeiro:
Generalizability of Graph Neural Networks for Decentralized Unlabeled Motion Planning. CoRR abs/2409.19829 (2024) - [i213]Liangzu Peng, Juan Elenter, Joshua Agterberg, Alejandro Ribeiro, René Vidal:
ICL-TSVD: Bridging Theory and Practice in Continual Learning with Pre-trained Models. CoRR abs/2410.00645 (2024) - [i212]Chen Liu, Danqi Liao, Alejandro Parada-Mayorga, Alejandro Ribeiro, Marcello DiStasio, Smita Krishnaswamy:
DiffKillR: Killing and Recreating Diffeomorphisms for Cell Annotation in Dense Microscopy Images. CoRR abs/2410.03058 (2024) - [i211]Ignacio Hounie, Charilaos I. Kanatsoulis, Arnuv Tandon, Alejandro Ribeiro:
LoRTA: Low Rank Tensor Adaptation of Large Language Models. CoRR abs/2410.04060 (2024) - [i210]Jiashu He, Mingyu Derek Ma, Jinxuan Fan, Dan Roth, Wei Wang, Alejandro Ribeiro:
GIVE: Structured Reasoning with Knowledge Graph Inspired Veracity Extrapolation. CoRR abs/2410.08475 (2024) - [i209]Alejandro Parada-Mayorga, Leopoldo Agorio, Alejandro Ribeiro, Juan Andrés Bazerque:
Convolutional Filtering with RKHS Algebras. CoRR abs/2411.01341 (2024) - 2023
- [j148]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): 1494-1507 (2023) - [j147]Harshat Kumar, Alec Koppel, Alejandro Ribeiro:
On the sample complexity of actor-critic method for reinforcement learning with function approximation. Mach. Learn. 112(7): 2433-2467 (2023) - [j146]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): 1321-1336 (2023) - [j145]Luiz F. O. Chamon, Santiago Paternain, Miguel Calvo-Fullana, Alejandro Ribeiro:
Constrained Learning With Non-Convex Losses. IEEE Trans. Inf. Theory 69(3): 1739-1760 (2023) - [j144]Max Wasserman, Saurabh Sihag, Gonzalo Mateos, Alejandro Ribeiro:
Learning Graph Structure from Convolutional Mixtures. Trans. Mach. Learn. Res. 2023 (2023) - [j143]Alejandro Parada-Mayorga, Zhiyang Wang, Fernando Gama, Alejandro Ribeiro:
Stability of Aggregation Graph Neural Networks. IEEE Trans. Signal Inf. Process. over Networks 9: 850-864 (2023) - [j142]Juan Cerviño, Luana Ruiz, Alejandro Ribeiro:
Learning by Transference: Training Graph Neural Networks on Growing Graphs. IEEE Trans. Signal Process. 71: 233-247 (2023) - [j141]Landon Butler, Alejandro Parada-Mayorga, Alejandro Ribeiro:
Convolutional Learning on Multigraphs. IEEE Trans. Signal Process. 71: 933-946 (2023) - [j140]Navid Naderializadeh, Mark Eisen, Alejandro Ribeiro:
Learning Resilient Radio Resource Management Policies With Graph Neural Networks. IEEE Trans. Signal Process. 71: 995-1009 (2023) - [j139]Alejandro Parada-Mayorga, Landon Butler, Alejandro Ribeiro:
Convolutional Filters and Neural Networks With Noncommutative Algebras. IEEE Trans. Signal Process. 71: 2683-2698 (2023) - [j138]Luana Ruiz, Luiz F. O. Chamon, Alejandro Ribeiro:
Transferability Properties of Graph Neural Networks. IEEE Trans. Signal Process. 71: 3474-3489 (2023) - [j137]Alejandro Parada-Mayorga, Zhiyang Wang, Alejandro Ribeiro:
Graphon Pooling for Reducing Dimensionality of Signals and Convolutional Operators on Graphs. IEEE Trans. Signal Process. 71: 3577-3591 (2023) - [c302]Zhiyang Wang, Luana Ruiz, Alejandro Ribeiro:
Convergence of Graph Neural Networks on Relatively Sparse Graphs. ACSSC 2023: 566-572 - [c301]Damian Owerko, Charilaos I. Kanatsoulis, Alejandro Ribeiro:
Solving Large-Scale Spatial Problems with Convolutional Neural Networks. ACSSC 2023: 1064-1069 - [c300]Damian Owerko, Charilaos I. Kanatsoulis, Jennifer Bondarchuk, Donald J. Bucci, Alejandro Ribeiro:
Multi-Target Tracking with Transferable Convolutional Neural Networks. CAMSAP 2023: 56-60 - [c299]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: 253-258 - [c298]Claudio Battiloro, Paolo Di Lorenzo, Alejandro Ribeiro:
Parametric Dictionary Learning for Topological Signal Representation. EUSIPCO 2023: 1958-1962 - [c297]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: 1-5 - [c296]Landon Butler, Alejandro Parada-Mayorga, Alejandro Ribeiro:
Learning with Multigraph Convolutional Filters. ICASSP 2023: 1-5 - [c295]Juan Cerviño, Juan Andrés Bazerque, Miguel Calvo-Fullana, Alejandro Ribeiro:
Multi-Task Bias-Variance Trade-Off Through Functional Constraints. ICASSP 2023: 1-5 - [c294]Juan Cerviño, Luana Ruiz, Alejandro Ribeiro:
Training Graph Neural Networks on Growing Stochastic Graphs. ICASSP 2023: 1-5 - [c293]Samar Hadou, Charilaos I. Kanatsoulis, Alejandro Ribeiro:
Space-Time Graph Neural Networks with Stochastic Graph Perturbations. ICASSP 2023: 1-5 - [c292]Ignacio Hounie, Juan Elenter, Alejandro Ribeiro:
Neural Networks with Quantization Constraints. ICASSP 2023: 1-5 - [c291]Harshat Kumar, Alejandro Parada-Mayorga, Alejandro Ribeiro:
Algebraic Convolutional Filters on Lie Group Algebras. ICASSP 2023: 1-5 - [c290]Saurabh Sihag, Gonzalo Mateos, Corey McMillan, Alejandro Ribeiro:
Predicting Brain Age Using Transferable Covariance Neural Networks. ICASSP 2023: 1-5 - [c289]Zhiyang Wang, Luana Ruiz, Alejandro Ribeiro:
Convolutional Filtering on Sampled Manifolds. ICASSP 2023: 1-5 - [c288]Juan Cerviño, Luiz F. O. Chamon, Benjamin David Haeffele, René Vidal, Alejandro Ribeiro:
Learning Globally Smooth Functions on Manifolds. ICML 2023: 3815-3854 - [c287]Ignacio Hounie, Luiz F. O. Chamon, Alejandro Ribeiro:
Automatic Data Augmentation via Invariance-Constrained Learning. ICML 2023: 13410-13433 - [c286]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: 3048-3055 - [c285]Mikhail Hayhoe, Hans Riess, Michael M. Zavlanos, Victor M. Preciado, Alejandro Ribeiro:
Transferable Hypergraph Neural Networks via Spectral Similarity. LoG 2023: 18 - [c284]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: 23 - [c283]Dongsheng Ding, Chen-Yu Wei, Kaiqing Zhang, Alejandro Ribeiro:
Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs. NeurIPS 2023 - [c282]Ignacio Hounie, Alejandro Ribeiro, Luiz F. O. Chamon:
Resilient Constrained Learning. NeurIPS 2023 - [c281]Saurabh Sihag, Gonzalo Mateos, Corey McMillan, Alejandro Ribeiro:
Explainable Brain Age Prediction using coVariance Neural Networks. NeurIPS 2023 - [c280]Igor Spasojevic, Xu Liu, Alejandro Ribeiro, George J. Pappas, Vijay Kumar:
Active Collaborative Localization in Heterogeneous Robot Teams. Robotics: Science and Systems 2023 - [i208]Elijah S. Lee, Lifeng Zhou, Alejandro Ribeiro, Vijay Kumar:
Graph Neural Networks for Decentralized Multi-Agent Perimeter Defense. CoRR abs/2301.09689 (2023) - [i207]Claudio Battiloro, Zhiyang Wang, Hans Riess, Paolo Di Lorenzo, Alejandro Ribeiro:
Tangent Bundle Convolutional Learning: from Manifolds to Cellular Sheaves and Back. CoRR abs/2303.11323 (2023) - [i206]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 abs/2305.01807 (2023) - [i205]Samar Hadou, Navid Naderializadeh, Alejandro Ribeiro:
Stochastic Unrolled Federated Learning. CoRR abs/2305.15371 (2023) - [i204]Igor Spasojevic, Xu Liu, Alejandro Ribeiro, George J. Pappas, Vijay Kumar:
Active Collaborative Localization in Heterogeneous Robot Teams. CoRR abs/2305.18193 (2023) - [i203]Saurabh Sihag, Gonzalo Mateos, Corey T. McMillan, Alejandro Ribeiro:
Explainable Brain Age Prediction using coVariance Neural Networks. CoRR abs/2305.18370 (2023) - [i202]Zhiyang Wang, Luana Ruiz, Alejandro Ribeiro:
Geometric Graph Filters and Neural Networks: Limit Properties and Discriminability Trade-offs. CoRR abs/2305.18467 (2023) - [i201]Ignacio Hounie, Alejandro Ribeiro, Luiz F. O. Chamon:
Resilient Constrained Learning. CoRR abs/2306.02426 (2023) - [i200]Damian Owerko, Charilaos I. Kanatsoulis, Alejandro Ribeiro:
Solving Large-scale Spatial Problems with Convolutional Neural Networks. CoRR abs/2306.08191 (2023) - [i199]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 abs/2306.08737 (2023) - [i198]Dongsheng Ding, Chen-Yu Wei, Kaiqing Zhang, Alejandro Ribeiro:
Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs. CoRR abs/2306.11700 (2023) - [i197]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 abs/2307.04962 (2023) - [i196]Damian Owerko, Charilaos I. Kanatsoulis, Jennifer Bondarchuk, Donald J. Bucci Jr., Alejandro Ribeiro:
Transferability of Convolutional Neural Networks in Stationary Learning Tasks. CoRR abs/2307.11588 (2023) - [i195]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 abs/2308.06658 (2023) - [i194]Saurav Agarwal, Alejandro Ribeiro, Vijay Kumar:
Asynchronous Perception-Action-Communication with Graph Neural Networks. CoRR abs/2309.10164 (2023) - [i193]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 abs/2309.14284 (2023) - [i192]Juan Elenter, Navid Naderializadeh, Tara Javidi, Alejandro Ribeiro:
Primal-Dual Continual Learning: Stability and Plasticity through Lagrange Multipliers. CoRR abs/2310.00154 (2023) - [i191]Sourajit Das, Navid Naderializadeh, Alejandro Ribeiro:
Learning State-Augmented Policies for Information Routing in Communication Networks. CoRR abs/2310.00248 (2023) - [i190]Jiashu He, Charilaos I. Kanatsoulis, Alejandro Ribeiro:
Network Alignment with Transferable Graph Autoencoders. CoRR abs/2310.03272 (2023) - [i189]Alejandro Parada-Mayorga, Landon Butler, Alejandro Ribeiro:
Non Commutative Convolutional Signal Models in Neural Networks: Stability to Small Deformations. CoRR abs/2310.03879 (2023) - [i188]Shervin Khalafi, Saurabh Sihag, Alejandro Ribeiro:
Neural Tangent Kernels Motivate Graph Neural Networks with Cross-Covariance Graphs. CoRR abs/2310.10791 (2023) - [i187]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 abs/2311.17847 (2023) - [i186]Samar Hadou, Navid Naderializadeh, Alejandro Ribeiro:
Robust Stochastically-Descending Unrolled Networks. CoRR abs/2312.15788 (2023) - [i185]Dongsheng Ding, Zhengyan Huan, Alejandro Ribeiro:
Resilient Constrained Reinforcement Learning. CoRR abs/2312.17194 (2023) - 2022
- [j136]Harshat Kumar, Santiago Paternain, Alejandro Ribeiro:
Navigation of a quadratic potential with ellipsoidal obstacles. Autom. 146: 110643 (2022) - [j135]Paul Brown, Mark Eisen, Santiago Segarra, Alejandro Ribeiro, Gabriel Egan:
How the Word Adjacency Network (WAN) works. Digit. Scholarsh. Humanit. 37(2): 321-335 (2022) - [j134]Elvin Isufi, Fernando Gama, Alejandro Ribeiro:
EdgeNets: Edge Varying Graph Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. 44(11): 7457-7473 (2022) - [j133]Daniel Mox, Vijay Kumar, Alejandro Ribeiro:
Learning Connectivity-Maximizing Network Configurations. IEEE Robotics Autom. Lett. 7(2): 5552-5559 (2022) - [j132]Zhan Gao, Fernando Gama, Alejandro Ribeiro:
Spherical convolutional neural networks: Stability to perturbations in SO(3). Signal Process. 196: 108529 (2022) - [j131]Vinícius Lima, Mark Eisen, Konstantinos Gatsis, Alejandro Ribeiro:
Model-Free design of control systems over wireless fading channels. Signal Process. 197: 108540 (2022) - [j130]Luiz F. O. Chamon, Alexandre Amice, Alejandro Ribeiro:
Approximately Supermodular Scheduling Subject to Matroid Constraints. IEEE Trans. Autom. Control. 67(3): 1384-1396 (2022) - [j129]Santiago Paternain, Juan Andrés Bazerque, Alejandro Ribeiro:
Policy Gradient for Continuing Tasks in Discounted Markov Decision Processes. IEEE Trans. Autom. Control. 67(9): 4467-4482 (2022) - [j128]Zhan Gao, Mark Eisen, Alejandro Ribeiro:
Resource Allocation via Model-Free Deep Learning in Free Space Optical Communications. IEEE Trans. Commun. 70(2): 920-934 (2022) - [j127]Ting-Kuei Hu, Fernando Gama, Tianlong Chen, Wenqing Zheng, Zhangyang Wang, Alejandro Ribeiro, Brian M. Sadler:
Scalable Perception-Action-Communication Loops With Convolutional and Graph Neural Networks. IEEE Trans. Signal Inf. Process. over Networks 8: 12-24 (2022) - [j126]Zhiyang Wang, Mark Eisen, Alejandro Ribeiro:
Learning Decentralized Wireless Resource Allocations With Graph Neural Networks. IEEE Trans. Signal Process. 70: 1850-1863 (2022) - [j125]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: 1932-1946 (2022) - [j124]Zhan Gao, Alec Koppel, Alejandro Ribeiro:
Balancing Rates and Variance via Adaptive Batch-Size for Stochastic Optimization Problems. IEEE Trans. Signal Process. 70: 3693-3708 (2022) - [j123]Zhan Gao, Fernando Gama, Alejandro Ribeiro:
Wide and Deep Graph Neural Network With Distributed Online Learning. IEEE Trans. Signal Process. 70: 3862-3877 (2022) - [j122]Navid Naderializadeh, Mark Eisen, Alejandro Ribeiro:
State-Augmented Learnable Algorithms for Resource Management in Wireless Networks. IEEE Trans. Signal Process. 70: 5898-5912 (2022) - [c279]Zhiyang Wang, Luana Ruiz, Alejandro Ribeiro:
Convolutional Neural Networks on Manifolds: From Graphs and Back.