Chunyan Miao
Artificial Intelligence · IEEE Communications Surveys and Tutorials · 2010–2022
A researcher in the Science corpus: 20 papers; trusts 1,276 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 497 citations into it; #21,538 of 35,345 by trust here, #4,956 by citations
- Computer Vision and Pattern Recognition — 358 citations into it; #18,384 of 21,575 by trust here, #7,092 by citations
- Computer Networks and Communications — 122 citations into it
- Representation & Self-Supervised Learning — 100 citations into it
- Electrical and Electronic Engineering — 77 citations into it
- Information Systems — 74 citations into it
- Optimization & Training — 61 citations into it
- Natural Language Processing — 56 citations into it
Whom Chunyan Miao trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Alex Krizhevsky
- Yoshua Bengio
- Kaiming He
- Diederik P. Kingma
- Ilya Sutskever
- Yann LeCun
- Ross B. Girshick
- Karen Simonyan
- Ruslan Salakhutdinov
Who trusts Chunyan Miao overall
Papers from Chunyan Miao's perspective
Ordered by how strongly the researchers Chunyan Miao trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Online multimodal deep similarity learning with application to image retrieval (2013) — 173 citations
- Learning to Segment the Tail (2020) — 93 citations
- Distilling Causal Effect of Data in Class-Incremental Learning (2021) — 213 citations
- A Survey of Zero-Shot Learning (2019) — 777 citations
- Building Ethics into Artificial Intelligence (2018) — 213 citations
- Incentive Mechanism Design for Resource Sharing in Collaborative Edge Learning (2020) — 26 citations
- Federated Learning in Mobile Edge Networks: A Comprehensive Survey (2019) — 2,306 citations
- Towards Federated Learning in UAV-Enabled Internet of Vehicles: A Multi-Dimensional Contract-Matching Approach (2020) — 273 citations
- Neighborhood Regularized Logistic Matrix Factorization for Drug-Target Interaction Prediction (2016) — 354 citations
- A Full Dive Into Realizing the Edge-Enabled Metaverse: Visions, Enabling Technologies, and Challenges (2022) — 468 citations
- Bootstrap Latent Representations for Multi-modal Recommendation (2022) — 370 citations
- Semantic Communications for Future Internet: Fundamentals, Applications, and Challenges (2022) — 646 citations
- Cycle-Consistent Inverse GAN for Text-to-Image Synthesis (2021) — 57 citations
- Weakly Supervised Segmentation with Maximum Bipartite Graph Matching (2020) — 42 citations
- EEG-Based Emotion Recognition Using Regularized Graph Neural Networks (2019) — 779 citations
- Knowledge-Enriched Transformer for Emotion Detection in Textual Conversations (2019) — 307 citations
- Online Multitask Relative Similarity Learning (2017) — 14 citations
- Distributed multi-task classification: a decentralized online learning approach (2017) — 30 citations
- Exploiting Geographical Neighborhood Characteristics for Location Recommendation (2014) — 355 citations
- A Survey of Trust and Reputation Management Systems in Wireless Communications (2010) — 323 citations