Osvaldo Simeone
Electrical and Electronic Engineering · 2007–2019
A researcher in the Science corpus: 13 papers; trusts 238 researchers and is trusted by 34 researchers here, as inferred from the citation graph.
Subfields
- Electrical and Electronic Engineering — 126 citations into it; #2,093 of 16,539 by trust here, #2,841 by citations
- Computer Networks and Communications — 108 citations into it; #939 of 9,886 by trust here, #540 by citations
- Artificial Intelligence — 74 citations into it; #8,298 of 35,345 by trust here, #14,181 by citations
- Aerospace Engineering — 30 citations into it; #2,684 of 6,421 by trust here, #1,499 by citations
- Computer Vision and Pattern Recognition — 26 citations into it
- Probabilistic & Bayesian Methods — 23 citations into it
- Computational Mechanics — 14 citations into it
- Optimization & Training — 13 citations into it
Whom Osvaldo Simeone trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Radford M. Neal
- Diederik P. Kingma
- Yoshua Bengio
- Ian J. Goodfellow
- Andriy Mnih
- Yann LeCun
- Kevin P. Murphy
- Alex Krizhevsky
- Dimitri P. Bertsekas
Who trusts Osvaldo Simeone overall
- Robin Chataut
- Solmaz Niknam
- Lefteris Benos
- Yong Zeng
- Robert Akl
- Yuxi Li
- Harpreet S. Dhillon
- Jihong Park
- Jemin Lee
- Alessio Zappone
Papers from Osvaldo Simeone's perspective
Ordered by how strongly the researchers Osvaldo Simeone trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Multi-Cell MIMO Cooperative Networks: A New Look at Interference (2010) — 1,784 citations
- 5G Wireless Network Slicing for eMBB, URLLC, and mMTC: A Communication-Theoretic View (2018) — 844 citations
- Mobile Edge Computing via a UAV-Mounted Cloudlet: Optimization of Bit Allocation and Path Planning (2016) — 596 citations
- Reconfigurable Intelligent Surfaces vs. Relaying: Differences, Similarities, and Performance Comparison (2019) — 657 citations
- Energy Harvesting Wireless Communications: A Review of Recent Advances (2015) — 856 citations
- Wireless Federated Distillation for Distributed Edge Learning with Heterogeneous Data (2019) — 129 citations
- Spectrum Leasing to Cooperating Secondary Ad Hoc Networks (2008) — 596 citations
- Stable Throughput of Cognitive Radios With and Without Relaying Capability (2007) — 376 citations
- Coded Federated Computing in Wireless Networks with Straggling Devices and Imperfect CSI (2019) — 41 citations
- Distributed and Private Coded Matrix Computation with Flexible Communication Load (2019) — 34 citations
- Semantic-Effectiveness Filtering and Control for Post-5G Wireless Connectivity (2019) — 124 citations
- A Very Brief Introduction to Machine Learning With Applications to Communication Systems (2018) — 456 citations
- A Brief Introduction to Machine Learning for Engineers (2017) — 158 citations