| Nome |
# |
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Distributed signal processing and optimization based on in-network subspace projections, file e3835325-22f2-15e8-e053-a505fe0a3de9
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280
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Joint resource allocation for latency-constrained dynamic computation offloading with MEC, file e3835325-a069-15e8-e053-a505fe0a3de9
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194
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Latency-constrained dynamic computation offloading with energy harvesting IoT devices, file e3835325-a05e-15e8-e053-a505fe0a3de9
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178
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A joint Markov model for communities, connectivity and signals defined over graphs, file e3835327-9f98-15e8-e053-a505fe0a3de9
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149
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Observing and tracking bandlimited graph processes from sampled measurements, file e3835327-d5f7-15e8-e053-a505fe0a3de9
|
99
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Energy-efficient classification at the wireless edge with reliability guarantees, file c3e8225e-3779-4ea6-82e2-a205975aeab7
|
51
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Dynamic resource optimization for adaptive federated learning empowered by reconfigurable intelligent surfaces, file c3cfb1aa-52a1-478e-aad6-f5633209ab93
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32
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Tangent Bundle Filters and Neural Networks: From Manifolds to Cellular Sheaves and Back, file 44af7fe6-298c-41dd-af45-4e0134642b7f
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25
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Topological Slepians: Maximally Localized Representations of Signals Over Simplicial Complexes, file 5901904f-fd9e-4dce-84d0-8b7fabeaa3f4
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23
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Lyapunov-based optimization of edge resources for energy-efficient adaptive federated learning, file 17bda8a3-d37b-46e8-a80b-e27a74fef086
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21
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Lyapunov-Driven Deep Reinforcement Learning for Edge Inference Empowered by Reconfigurable Intelligent Surfaces, file 0d5ff4ec-b80e-4439-bc8b-eb9022627936
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20
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Multiscale causal structure learning, file 51ad7176-6271-47cc-98c5-ba822426e59a
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19
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Goal-Oriented Communication for Edge Learning Based On the Information Bottleneck, file 51f08e5d-7ea1-4552-8a64-ce5e95e53f64
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18
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Topological signal processing over weighted simplicial complexes, file c7d10700-795f-4c38-8e07-37bb8050e95e
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18
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Dynamic Ensemble Inference at the Edge, file 438f592a-0511-43b6-8073-7ad473e23c6b
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16
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Pooling strategies for simplicial convolutional networks, file 928a0189-83f3-4796-8b4b-0b955a5960aa
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16
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Discontinuous computation offloading for energy-efficient mobile edge computing, file e383532e-6444-15e8-e053-a505fe0a3de9
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14
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Multi-user goal-oriented communications with energy-efficient edge resource management, file 376423ea-d5c6-4d6d-9b79-f52ee0ac400c
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12
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Dynamic resource optimization for decentralized estimation in energy harvesting IoT networks, file e3835328-e053-15e8-e053-a505fe0a3de9
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12
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Reconfigurable Intelligent Surface Aided Mobile Edge Computing over Intermittent mmWave Links, file fabd43f4-9fc8-4267-86f3-49402ed3a83b
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10
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Wireless environment as a service enabled by reconfigurable intelligent surfaces: The RISE-6G perspective, file e383532e-75fe-15e8-e053-a505fe0a3de9
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9
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Distributed Sum-Rate Maximization of Cellular Communications with Multiple Reconfigurable Intelligent Surfaces, file ea04d963-fae4-4782-8f67-3bda6aecb90e
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8
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Distributed signal processing and optimization based on in-network subspace projections, file e3835326-95a1-15e8-e053-a505fe0a3de9
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7
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Adaptive resource optimization for edge inference with goal-oriented communications, file 89ee454e-5b64-4caf-87b3-b22961dd62d3
|
6
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Sampling and recovery of graph signals, file e383531c-7f9e-15e8-e053-a505fe0a3de9
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6
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Graph topology inference based on sparsifying transform learning, file e3835320-2261-15e8-e053-a505fe0a3de9
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6
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Wireless edge machine learning. Resource allocation and trade-offs, file e383532e-75fb-15e8-e053-a505fe0a3de9
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6
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Distributed semi-supervised support vector machines, file e3835314-be1d-15e8-e053-a505fe0a3de9
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5
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Distributed data clustering over networks, file e3835323-1818-15e8-e053-a505fe0a3de9
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5
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Dynamic edge computing empowered by reconfigurable intelligent surfaces, file ed8a30b9-c2ab-4bff-99fb-228d8eb3575e
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5
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RIS-enabled smart wireless environments: deployment scenarios, network architecture, bandwidth and area of influence, file 87663895-58e0-4f19-bd0c-c18ad5fcb334
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4
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On the graph Fourier transform for directed graphs, file e383531f-dc53-15e8-e053-a505fe0a3de9
|
4
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Dynamic computation offloading in multi-access edge computing via ultra-reliable and low-latency communications, file e3835325-2158-15e8-e053-a505fe0a3de9
|
4
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Dynamic computation offloading in multi-access edge computing via ultra-reliable and low-latency communications, file e3835327-fe6e-15e8-e053-a505fe0a3de9
|
4
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Graph topology inference based on transform learning, file e3835328-29c3-15e8-e053-a505fe0a3de9
|
4
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Goal-Oriented Communications for the IoT: System Design and Adaptive Resource Optimization, file fb397d84-99d8-4ace-873f-8991f8888536
|
4
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Bio-Inspired Dynamic Radio Access in Cognitive Networks based on Social Foraging Swarms, file e3835316-0343-15e8-e053-a505fe0a3de9
|
3
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Distributed adaptive learning of graph signals, file e383531e-56bb-15e8-e053-a505fe0a3de9
|
3
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Enabling prediction via multi-layer graph inference and sampling, file e3835325-aa1b-15e8-e053-a505fe0a3de9
|
3
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Dynamic resource allocation for wireless edge machine learning with latency and accuracy guarantees, file e3835325-c3ae-15e8-e053-a505fe0a3de9
|
3
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Distributed signal recovery based on in-network subspace projections, file e3835325-d33a-15e8-e053-a505fe0a3de9
|
3
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Semantic Communications Based on Adaptive Generative Models and Information Bottleneck, file b26e3fda-f7d1-4ff4-b267-5b21bb2a0c4f
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2
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Reducing the in band network telemetry overhead through the spatial sampling. Theory and experimental results, file b6efae75-eecf-4f5b-af03-69d12c097553
|
2
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Communicating while computing: Distributed mobile cloud computing over 5G heterogeneous networks, file e3835312-6b1d-15e8-e053-a505fe0a3de9
|
2
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|
Parallel and distributed training of neural networks via successive convex approximation, file e3835317-3e11-15e8-e053-a505fe0a3de9
|
2
|
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Swarming algorithms for distributed radio resource allocation: a further step in the direction of an ever-deeper synergism between biological mathematical modeling and signal processing, file e383531a-f0a0-15e8-e053-a505fe0a3de9
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2
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Distributed detection and estimation in wireless sensor networks, file e383531c-75a4-15e8-e053-a505fe0a3de9
|
2
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Optimal beamforming for range-doppler ambiguity minimization in squinted SAR, file e383531c-92ec-15e8-e053-a505fe0a3de9
|
2
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Parameter estimation of 2D multi-component polynomial phase signals: an application to SAR imaging of moving targets, file e383531c-9db6-15e8-e053-a505fe0a3de9
|
2
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Distributed stochastic nonconvex optimization and learning based on successive convex approximation, file e3835327-fe74-15e8-e053-a505fe0a3de9
|
2
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Dynamic resource optimization for decentralized signal estimation in energy harvesting wireless sensor networks, file e3835328-122f-15e8-e053-a505fe0a3de9
|
2
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Distributed tensor completion over networks, file e3835328-3e4e-15e8-e053-a505fe0a3de9
|
2
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Online learning of time-varying signals and graphs, file e383532d-feb7-15e8-e053-a505fe0a3de9
|
2
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Dynamic Resource Allocation for Multi-User Goal-oriented Communications at the Wireless Edge, file 19e0b54a-435c-4308-8b95-f6bd1c807b12
|
1
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Power minimizing mec offloading with qos constraints over ris-empowered communications, file 4363e9bc-abe5-4516-9a6e-fbebf893874c
|
1
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Analog versus digital pulse amplitude modulation for goal-oriented wireless communications, file 663ab502-ff96-43a9-8dcd-43f8b0bdca88
|
1
|
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In Band Network Telemetry Overhead Reduction Based on Data Flows Sampling and Recovering, file 8e496209-9a4e-46ab-ba6b-0e5f678c073d
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1
|
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Parametric dictionary learning for topological signal representation, file ae0bc77f-6639-465e-a5a6-adadc2a07be9
|
1
|
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A framework for parallel and distributed training of neural networks, file e3835317-2d4d-15e8-e053-a505fe0a3de9
|
1
|
|
Graph Fourier transform for directed graphs based on Lovász extension of min-cut, file e3835319-6818-15e8-e053-a505fe0a3de9
|
1
|
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Optimal sampling strategies for adaptive learning of graph signals, file e3835319-681b-15e8-e053-a505fe0a3de9
|
1
|
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Distributed recursive least squares strategies for adaptive reconstruction of graph signals, file e3835319-681c-15e8-e053-a505fe0a3de9
|
1
|
|
Sparse distributed learning based on diffusion adaptation, file e383531b-028d-15e8-e053-a505fe0a3de9
|
1
|
|
Distributed sum-rate maximization over finite rate coordination links affected by random failures, file e383531b-0b20-15e8-e053-a505fe0a3de9
|
1
|
|
Distributed nonconvex optimization over time-varying networks, file e383531b-254a-15e8-e053-a505fe0a3de9
|
1
|
|
Adaptive Least Mean Squares Estimation of Graph Signals, file e383531b-4dbe-15e8-e053-a505fe0a3de9
|
1
|
|
Decentralized resource assignment in cognitive networks based on swarming mechanisms over random graphs, file e383531c-7fae-15e8-e053-a505fe0a3de9
|
1
|
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Bio-inspired decentralized radio access based on swarming mechanisms over adaptive networks, file e383531c-8390-15e8-e053-a505fe0a3de9
|
1
|
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Stochastic training of neural networks via successive convex approximations, file e383531c-92d7-15e8-e053-a505fe0a3de9
|
1
|
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Adaptive graph signal processing: algorithms and optimal sampling strategies, file e383531c-92dd-15e8-e053-a505fe0a3de9
|
1
|
|
A bio-inspired swarming algorithm for decentralized access in cognitive radio, file e383531c-b4d7-15e8-e053-a505fe0a3de9
|
1
|
|
Dynamic joint resource allocation and user assignment in multi-access edge computing, file e3835322-6aa6-15e8-e053-a505fe0a3de9
|
1
|
|
Computation offloading strategies based on energy minimization under computational rate constraints, file e3835322-ac08-15e8-e053-a505fe0a3de9
|
1
|
|
Fast simulation performance evaluation of spaceborne SAR-GMTI missions for maritime applications, file e3835323-7b9f-15e8-e053-a505fe0a3de9
|
1
|
|
Decentralized estimation and control of algebraic connectivity of random ad-hoc networks, file e3835323-7bac-15e8-e053-a505fe0a3de9
|
1
|
|
Distributed adaptive learning of signals defined over graphs, file e3835325-110a-15e8-e053-a505fe0a3de9
|
1
|
|
Network energy efficient mobile edge computing with reliability guarantees, file e3835325-85e3-15e8-e053-a505fe0a3de9
|
1
|
|
Distributed adaptive learning of graph processes via in-network subspace projections, file e3835325-d2ed-15e8-e053-a505fe0a3de9
|
1
|
|
Observing bandlimited graph processes from subsampled measurements, file e3835328-0c68-15e8-e053-a505fe0a3de9
|
1
|
|
A joint Markov model for communities, connectivity and signals defined over graphs, file e3835328-53b3-15e8-e053-a505fe0a3de9
|
1
|
|
Distributed training of graph convolutional networks, file e3835329-74bd-15e8-e053-a505fe0a3de9
|
1
|
|
Distributed training of graph convolutional networks, file e3835329-74be-15e8-e053-a505fe0a3de9
|
1
|
| Totale |
1.362 |