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Z. Gao, F. Gama and A. Ribeiro, ”Stability of Spherical Convolutional Neural Networks to Rotation Diffeomorphisms,”
T. K. Hu, F. Gama, T. Chen, Z. Wang, A. Ribeiro and B. M. Sadler, ”VGAI: End-to-End Learning of Vision-Based Decentralized Controllers for Robot Swarms,”
F. Gama, E. Tolstaya and A. Ribeiro, ”Graph Neural Networks for Decentralized Controllers,”
Z. Gao, F. Gama and A. Ribeiro, ”Wide and Deep Graph Neural Networks with Distributed Online Learning,”
S. Pfrommer, A. Ribeiro and F. Gama, ”Discriminability of Single-Layer Graph Neural Networks,”
A. Parada-Mayorga and A. Ribeiro, ”Stability of Algebraic Neural Networks to Small Perturbations,”
L. Ruiz, F. Gama, A. Ribeiro and E. Isufi, ”Nonlinear State-Space Generalizations of Graph Convolutional Neural Networks,”
Z. Wang, M. Eisen and A. Ribeiro, ”Unsupervised Learning for Asynchronous Resource Allocation In Ad-Hoc Wireless Networks,”
L. Ruiz, Z. Wang and A. Ribeiro, ”Graphon and Graph Neural Network Stability,”
Z. Gao, E. Isufi and A. Ribeiro, ”Variance-Constrained Learning for Stochastic Graph Neural Networks,”
Juan Cervino, L. Ruiz and A. Ribeiro, ”Increase and Conquer: Training Graph Neural Networks on Growing Graphs,”
L. Ruiz, L. F. O. Chamon and A. Ribeiro, ”Graphon Filters: Signal Processing in Very Large Graphs,”
D. S. Kalogerias, M. Eisen, G. J. Pappas and A. Ribeiro, ”Almost-Zero Duality Gaps in Model-Free Resource Allocation for Wireless Systems,”
A. Parada-Mayorga, L. Ruiz and A. Ribeiro, ”Graphon Pooling in Graph Neural Networks,”
Juan Cervino, J. A. Bazerque, M. Calvo-Fullana and A. Ribeiro, ”Multi-task Supervised Learning via Cross-learning,”
L. Zhou, V. D. Sharma, Q. Li, A. Prorok, A. Ribeiro and V. Kumar, ”Graph Neural Networks for Decentralized Multi-Robot Submodular Action Selection,”
A. Parada-Mayorga, H. Riess, A. Ribeiro and R. Ghrist, ”Quiver Signal Processing (QSP),”
A. Tsiamis, D. S. Kalogerias, L. F. O. Chamon, A. Ribeiro and G. J. Pappas, ”Risk-Constrained Linear-Quadratic Regulators,”
L. F. O. Chamon, A. Amice, S. Paternain and A. Ribeiro, ”Resilient Control: Compromising to Adapt,”
V. Lima, M. Eisen and A. Ribeiro, ”Learning Constrained Resource Allocation Policies in Wireless Control Systems,”
Z. Wang, M. Eisen and A. Ribeiro, ”Decentralized Wireless Resource Allocation with Graph Neural Networks,”
Q. Li, F. Gama, A. Ribeiro and A. Prorok, ”Graph Neural Networks for Decentralized Multi-Robot Path Planning,”
B. Iancu, L. Ruiz, A. Ribeiro and E. Isufi, ”Graph-Adaptive Activation Functions for Graph Neural Networks,”
M. Jahani, X. He, C. Ma, A. Mokhtari, D. Mudigere, A. Ribeiro and M. Takac, ”Efficient Distributed Hessian Free Algorithm for Large-scale Empirical Risk Minimization via Accumulating Sample Strategy,”
H. Kumar, S. Paternain and A. Ribeiro, ”Navigation of a Quadratic Potential with Star Obstacles,”
L. F. O. Chamon, S. Paternain and A. Ribeiro, ”Counterfactual Programming for Optimal Control,”
V. Lima, M. Eisen, K. Gatsis and A. Ribeiro, ”Resource Allocation in Large-Scale Wireless Control Systems with Graph Neural Networks ,”
L. F. O. Chamon and A. Ribeiro, ”Probably Approximately Correct Constrained Learning,”
L. Ruiz, L. F. O. Chamon and A. Ribeiro, ”Graphon Neural Networks and the Transferability of Graph Neural Networks,”
M. Eisen, M. M. Rashid, D. Cavalcanti and A. Ribeiro, ”Control-Aware Scheduling for Low Latency Wireless Systems with Deep Learning,”
M. Eisen, M. M. Rashid, A. Ribeiro and D. Cavalcanti, ”Scheduling Low Latency Traffic for Wireless Control Systems in 5G Networks,”
Z. Shen, Z. Wang, A. Ribeiro and H. Hassani, ”Sinkhorn Barycenter via Functional Gradient Descent,”
A. Khan, E. Tolstaya, A. Ribeiro and V. Kumar, ”Graph Policy Gradients for Large Scale Robot Control,”
C. Zhang, A. Khan, S. Paternain and A. Ribeiro, ”Sufficiently Accurate Model Learning,”
D. Owerko, F. Gama and A. Ribeiro, ”Optimal Power Flow Using Graph Neural Networks,”
D. Mox, M. Calvo-Fullana, M. Gerasimenko, J. Fink, V. Kumar and A. Ribeiro, ”Mobile Wireless Network Infrastructure on Demand,”
D. S. Kalogerias, L. F. O. Chamon, G. J. Pappas and A. Ribeiro, ”Better Safe Than Sorry: Risk-Aware Nonlinear Bayesian Estimation,”
D. S. Kalogerias, M. Eisen, G. J. Pappas and A. Ribeiro, ”A Zeroth-Order Learning Algorithm for Ergodic Optimization of Wireless Systems with no Models and no Gradients,”
F. Gama, J. Bruna and A. Ribeiro, ”Stability of Graph Neural Networks to Relative Perturbations,”
L. Ruiz, L. F. O. Chamon and A. Ribeiro, ”The Graphon Fourier Transform,”
L. Ruiz, F. Gama and A. Ribeiro, ”Spatial Gating Strategies for Graph Recurrent Neural Networks,”
M. Peifer and A. Ribeiro, ”Federated Classification with Low Complexity Reproducing Kernel Hilbert Space Representations,”
M. Eisen and A. Ribeiro, ”Transferable Policies for Large Scale Wireless Networks with Graph Neural Networks,”
N. Naderializadeh, M. Eisen and A. Ribeiro, ”Wireless Power Control via Counterfactual Optimization of Graph Neural Networks,”
Q. Li, F. Gama, A. Ribeiro and A. Prorok, ”Graph Neural Networks for Decentralized Path Planning,”
S. Segarra, T. M. Roddenberry, F. Memoli and A. Ribeiro, ”Metric Representations of Networks: A Uniqueness Result,”
V. Lima, M. Eisen, K. Gatsis and A. Ribeiro, ”Resource Allocation in Wireless Control Systems via Deep Policy Gradient,”
Z. Gao, E. Isufi and A. Ribeiro, ”Stochastic Graph Neural Networks,”
Z. Gao, A. Koppel and A. Ribeiro, ”Balancing Rates and Variance via Adaptive Batch-Sizes in First-Order Stochastic Optimization,”
Z. Shen, Z. Wang, A. Ribeiro and H. Hassani, ”Sinkhorn Natural Gradient for Generative Models,”
M. Calvo-Fullana, D. Mox, A. Pyattaev, J. Fink, V. Kumar and A. Ribeiro, ”ROS-NetSim: A Framework for the Integration of Robotic and Network Simulators,”
L. F. O. Chamon, S. Paternain, M. Calvo-Fullana and A. Ribeiro, ”The Empirical Duality Gap of Constrained Statistical Learning,”
Z. Gao, M. Eisen and A. Ribeiro, ”Resource Allocation via Graph Neural Networks in Free Space Optical Fronthaul Networks,”
Z. Gao, A. Koppel and A. Ribeiro, ”Incremental Greedy BFGS: An Incremental Quasi-Newton Method with Explicit Superlinear Rate,”
F. Gama, J. Bruna and A. Ribeiro, ”Stability of Graph Scattering Transforms,”
H. Kumar, A. Koppel and A. Ribeiro, ”On the Sample Complexity of Actor-Critic for Reinforcement Learning,”
L. F. O. Chamon, A. Amice and A. Ribeiro, ”Matroid-Constrained Approximately Supermodular Optimization for Near-Optimal Actuator Scheduling,”
S. Paternain, M. Morari and A. Ribeiro, ”Real-Time Model Predictive Control Based on Prediction-Correction Algorithms,”
S. Paternain, J. A. Bazerque, A. Small and A. Ribeiro, ”Policy Improvement Directions for Reinforcement Learning in Reproducing Kernel Hilbert Spaces,”
S. Paternain, S. Lee, M. M. Zavlanos and A. Ribeiro, ”Constrained Online Learning in Networks with Sublinear Regret and Fit,”
Z. Gao, M. Eisen and A. Ribeiro, ”Optimal WDM Power Allocation via Deep Learning for Radio on Free Space Optics Systems,”
F. Gama, A. G. Marques, G. Leus and A. Ribeiro, ”Convolutional Graph Neural Networks,”
L. F. O. Chamon, S. Paternain and A. Ribeiro, ”Learning Gaussian Processes with Bayesian Posterior Optimization,”
M. Coutino, E. Isufi, F. Gama, A. Ribeiro and G. Leus, ”Design Strategies for Sparse Control of Random Time-Varying Networks,”
M. Calvo-Fullana, F. Dagefu, B. M. Sadler and A. Ribeiro, ”Multi-mode Autonomous Communication Systems,”
S. Paternain, M. Calvo-Fullana, L. F. O. Chamon and A. Ribeiro, ”Learning Safe Policies via Primal-Dual Methods,”
E. Tolstaya, F. Gama, J. Paulos, G. J. Pappas, V. Kumar and A. Ribeiro, ”Learning Decentralized Controllers for Robot Swarms with Graph Neural Networks,”
S. Paternain, L. F. O. Chamon, M. Calvo-Fullana and A. Ribeiro, ”Constrained Reinforcement Learning Has Zero Duality Gap,”
A. KhanV. Kumar and A. Ribeiro, and and , ”Graph Policy Gradients for Large Scale Unlabeled Motion Planning with Constraints,”
E. Isufi, F. Gama and A. Ribeiro, ”Generalizing Graph Convolutional Neural Networks with Edge-Variant Recursions on Graphs,”
L. Ruiz, F. Gama and A. Ribeiro, ”Gated Graph Convolutional Recurrent Neural Networks,”
H. Kumar, S. Paternain and A. Ribeiro, ”Navigation of a Quadratic Potential with Ellipsoidal Obstacles,”
A. Khan, C. Zhang, S. Li, J. Wu, B. Schlotfeldt, S. Tang, A. Ribeiro, O. Bastani and V. Kumar, ”Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints,”
Juan Cervino, J. A. Bazerque, M. Calvo-Fullana and A. Ribeiro, ”Meta-Learning through Coupled Optimization in Reproducing Kernel Hilbert Spaces,”
M. Eisen and A. Ribeiro, ”Large Scale Wireless Power Allocation with Graph Neural Networks,”
S. Paternain, M. Fazlyab, V. Preciado and A. Ribeiro, ”A Prediction-Correction Primal-Dual Algorithm for Distributed Optimization,”
T. R. Godbole, M. Calvo-Fullana, A. Pyattaev, D. Mox, Sergey Andreev, A. Ribeiro and M. Valkama, ”Modeling mmWave Channels in High-Fidelity Simulations of Unmanned Aerial Systems,”
V. Lima, L. F. O. Chamon and A. Ribeiro, ”Model Predictive Selection: A Receding Horizon Scheme for Actuator Selection,”
F. Gama, A. G. Marques, A. Ribeiro and G. Leus, ”Aggregation Graph Neural Networks,”
F. Gama, A. Ribeiro and J. Bruna, ”Diffusion Scattering Transforms on Graphs,”
L. Ruiz, F. Gama, A. G. Marques and A. Ribeiro, ”Median Activation Functions for Graph Neural Networks,”
L. F. O. Chamon, Y. Eldar and A. Ribeiro, ”Sparse Recovery over Nonlinear Dictionaries,”
M. Peifer, L. F. O. Chamon, S. Paternain and A. Ribeiro, ”Sparse Learning of Parsimonious Reproducing Kernel Hilbert Space Models,”
M. Eisen, C. Zhang, L. F. O. Chamon, D. D. Lee and A. Ribeiro, ”Dual Domain Learning of Optimal Resource Allocations in Wireless Systems,”
M. Eisen, M. M. Rashid, K. Gatsis, D. Cavalcanti, N. Himayat and A. Ribeiro, ”Control Aware Communication Design for Time Sensitive Wireless Systems,”
E. Tolstaya, A. Ribeiro, V. Kumar and A. Kapoor, ”Inverse Optimal Planning for Air Traffic Control,”
Z. Shen, H. Hassani, C. Mi, H. Qian and A. Ribeiro, ”Hessian Aided Policy Gradient,”
S. Paternain, J. A. Bazerque, A. Small and A. Ribeiro, ”Learning Policies for Markov Decision Processes in Continuous Spaces,”
S. Paternain, A. Mokhtari and A. Ribeiro, ”A Newton Method for Faster Navigation in Cluttered Environments,”
W. Huang, Y. Wang, L. Zhou, E. Zhao, Y. Yuan and A. Ribeiro, ”Modeling Treatment Delays for Patients using Feature Label Pairs in a Time Series,”
D. Owerko, F. Gama and A. Ribeiro, ”Predicting Power Outages Using Graph Neural Networks,”
F. Gama, A. G. Marques, G. Leus and A. Ribeiro, ”CNN Architectures for Graph Data,”
A. Koppel, S. Paternain, C. Richard and A. Ribeiro, ”Decentralized Online Nonparametric Learning,”
E. Tolstaya, E. Stump, A. Koppel and A. Ribeiro, ”Composable Learning with Sparse Kernel Representations,”
M. Peifer, L. F. O. Chamon, S. Paternain and A. Ribeiro, ”Locally Adaptive Kernel Estimation Using Sparse Functional Programming,”
M. Eisen, C. Zhang, L. F. O. Chamon, D. D. Lee and A. Ribeiro, ”Online Deep Learning in Wireless Communication Systems,”
F. Gama, A. G. Marques, A. Ribeiro and G. Leus, ”MIMO Graph Filters for Convolutional Neural Networks,”
F. Gama, G. Leus, A. G. Marques and A. Ribeiro, ”Convolutional Neural Networks via Node-Varying Graph Filters,”
M. Fazlyab, S. Paternain, A. Ribeiro and V. Preciado, ”Distributed Smooth and Strongly Convex Optimization with Inexact Dual Methods,”
M. Eisen, K. Gatsis, G. J. Pappas and A. Ribeiro, ”Optimization of Switched Linear Systems Over Non-Stationary Wireless Channels,”
M. Eisen, K. Gatsis, G. J. Pappas and A. Ribeiro, ”Learning in Non-Stationary Wireless Control Systems via Newton’s Method,”
S. Paternain, M. Morari and A. Ribeiro, ”A Prediction-Correction Method for Model Predictive Control,”
A. Koppel, A. Mokhtari and A. Ribeiro, ”Parallel Stochastic Successive Convex Approximation Method for Large-Scale Dictionary Learning,”
A. Koppel, E. Tolstaya, E. Stump and A. Ribeiro, ”Nonparametric Stochastic Compositional Gradient Descent for Q-Learning in Continuous Markov Decision Problems,”
F. Gama, E. Isufi, G. Leus and A. Ribeiro, ”Control of Graph Signals Over Random Time-Varying Graphs,”
L. F. O. Chamon, Y. Eldar and A. Ribeiro, ”Strong Duality of Sparse Functional Optimization,”
M. Eisen, K. Gatsis, G. J. Pappas and A. Ribeiro, ”Learning Statistically Accurate Resource Allocations in Non-Stationary Wireless Systems,”
M. Eisen, A. Mokhtari and A. Ribeiro, ”Large Scale Empirical Risk Minimization via Truncated Adaptive Newton Method,”
W. Huang, A. G. Marques and A. Ribeiro, ”Matrix completion via graph signal processing,”
W. Huang, T. Bolton, J. Medaglia, D. S. Bassett, A. Ribeiro and D. Van De Ville, ”Graph Signal Processing of Human Brain Imaging Data,”
A. Khan, V. Kumar and A. Ribeiro, ”Learning Sample-Efficient Target Reaching for Mobile Robots,”
A. Mokhtari and A. Ribeiro, ”First-Order Adaptive Sample Size Methods to Reduce Complexity of Empirical Risk Minimization,”
L. F. O. Chamon, G. J. Pappas and A. Ribeiro, ”The mean square error in Kalman filtering sensor selection is approximately supermodular,”
S. Paternain and A. Ribeiro, ”Safe online navigation of convex potentials in spaces with convex obstacles,”
S. Segarra, A. G. Marques, G. R. Arce and A. Ribeiro, ”Design of weighted median graph filters,”
A. Koppel, S. Paternain, C. Richard and A. Ribeiro, ”Decentralized efficient nonparametric stochastic optimization,”
F. Gama and A. Ribeiro, ”Distributed estimation of smooth graph power spectral density,”
L. F. O. Chamon and A. Ribeiro, ”Approximate Supermodularity Bounds for Experimental Design,”
L. F. O. Chamon and A. Ribeiro, ”Finite-precision effects on graph filters,”
M. Fazlyab, A. Ribeiro, M. Morari and V. Preciado, ”A dynamical systems perspective to convergence rate analysis of proximal algorithms,”
M. Eisen, A. Mokhtari and A. Ribeiro, ”A primal-dual Quasi-Newton method for consensus optimization,”
W. Huang and A. Ribeiro, ”Partial embedding distance for networks,”
W. Huang, A. G. Marques and A. Ribeiro, ”Collaborative filtering via graph signal processing,”
M. Fazlyab, A. Koppel, V. Preciado and A. Ribeiro, ”A variational approach to dual methods for constrained convex optimization,”
M. Calvo-Fullana, C. Anton-Haro, J. Matamoros and A. Ribeiro, ”Random Access Policies for Wireless Networked Control Systems with Energy Harvesting Sensors,”
A. Koppel, G. Warnell, E. Stump and A. Ribeiro, ”Parsimonious Online Learning with Kernels via sparse projections in function space,”
A. Mokhtari, M. Eisen and A. Ribeiro, ”An incremental quasi-Newton method with a local superlinear convergence rate,”
A. Mokhtari, M. Gurbuzbalaban and A. Ribeiro, ”A double incremental aggregated gradient method with linear convergence rate for large-scale optimization,”
A. Mokhtari, A. Koppel, G. Scutari and A. Ribeiro, ”Large-scale nonconvex stochastic optimization by Doubly Stochastic Successive Convex approximation,”
F. Gama and A. Ribeiro, ”Weak law of large numbers for stationary graph processes,”
L. Goldsberry, W. Huang, N. Wymbs, S. Grafton, D. S. Bassett and A. Ribeiro, ”Brain signal analytics from graph signal processing perspective,”
L. F. O. Chamon and A. Ribeiro, ”Universal bounds for the sampling of graph signals,”
M. Calvo-Fullana, J. Matamoros, C. Anton-Haro and A. Ribeiro, ”Stochastic Backpressure in Energy Harvesting Networks,”
S. Segarra, A. G. Marques, G. Leus and A. Ribeiro, ”Stationary graph processes: Parametric power spectral estimation,”
S. Segarra, A. G. Marques, G. Mateos and A. Ribeiro, ”Robust network topology inference,”
W. Huang and A. Ribeiro, ”Axiomatic hierarchical clustering given intervals of metric distances,”
C. Eksin, P. Molavi, A. Ribeiro and A. Jadbabaie, ”Bayesian Quadratic Network Game Filters,”
G. Carlsson, F. Memoli, A. Ribeiro and S. Segarra, ”Axiomatic Construction of Hierarchical Clustering in Asymmetric Networks,”
