Peilin Zhao
Artificial Intelligence · AAAI Conference on Artificial Intelligence · 2010–2023
A researcher in the Science corpus: 29 papers; trusts 1,193 researchers and is trusted by 61 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 592 citations into it; #3,552 of 35,345 by trust here, #3,797 by citations
- Computer Vision and Pattern Recognition — 361 citations into it; #7,378 of 21,575 by trust here, #4,525 by citations
- Optimization & Training — 174 citations into it; #546 of 2,601 by trust here, #1,195 by citations
- Representation & Self-Supervised Learning — 118 citations into it
- Computer Networks and Communications — 111 citations into it
- Management Science and Operations Research — 107 citations into it; #757 of 11,946 by trust here, #1,243 by citations
- Computational Mechanics — 71 citations into it; #873 of 10,001 by trust here, #2,032 by citations
- Reinforcement Learning — 63 citations into it
Whom Peilin Zhao trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Tong Zhang
- Shai Shalev-Shwartz
- Geoffrey E. Hinton
- Yoshua Bengio
- Alex Krizhevsky
- Yann LeCun
- Kaiming He
- Diederik P. Kingma
- John C. Duchi
- Yoav Freund
Who trusts Peilin Zhao overall
- Jakub Konecný
- Cheng Zhang
- Peter Richtárik
- Sebastian U. Stich
- Steven C. H. Hoi
- Siddharth Gopal
- Filip Hanzely
- Kumar Kshitij Patel
- Ahmed Khaled
- Yuchen Zhang
Papers from Peilin Zhao's perspective
Ordered by how strongly the researchers Peilin Zhao 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)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Online multimodal deep similarity learning with application to image retrieval (2013) — 173 citations
- Local features are not lonely – Laplacian sparse coding for image classification (2010) — 472 citations
- Graph Convolutional Networks for Temporal Action Localization (2019) — 542 citations
- Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation (2021) — 35 citations
- Stochastic Optimization with Importance Sampling for Regularized Loss Minimization (2014) — 390 citations
- NAT: Neural Architecture Transformer for Accurate and Compact Architectures (2019) — 101 citations
- Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum Search (2020) — 78 citations
- Accelerating Minibatch Stochastic Gradient Descent using Stratified Sampling (2014) — 98 citations
- Decentralized Online Learning: Take Benefits from Others’ Data without Sharing Your Own to Track Global Trend (2019) — 19 citations
- Online Learning: A Comprehensive Survey (2018) — 832 citations
- Neighborhood Regularized Logistic Matrix Factorization for Drug-Target Interaction Prediction (2016) — 354 citations
- Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks (2020) — 816 citations
- Mastering Complex Control in MOBA Games with Deep Reinforcement Learning (2019) — 410 citations
- Supervised Learning Achieves Human-Level Performance in MOBA Games: A Case Study of Honor of Kings (2020) — 60 citations
- Towards Stable Test-Time Adaptation in Dynamic Wild World (2023) — 531 citations
- Efficient Test-Time Model Adaptation without Forgetting (2022) — 647 citations
- FedML: A Research Library and Benchmark for Federated Machine Learning (2020) — 716 citations
- Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis (2019) — 188 citations
- Confidence Weighted Multitask Learning (2019) — 7 citations
- From Whole Slide Imaging to Microscopy: Deep Microscopy Adaptation Network for Histopathology Cancer Image Classification (2019) — 70 citations