Xiaobo Xia
Artificial Intelligence · 2019–2021
A researcher in the Science corpus: 3 papers; trusts 44 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 93 citations into it
- Computer Vision and Pattern Recognition — 54 citations into it
- Optimization & Training — 40 citations into it
- Safety, Robustness & Interpretability — 18 citations into it
- Statistical Learning Theory — 16 citations into it
- Representation & Self-Supervised Learning — 13 citations into it
- Natural Language Processing — 9 citations into it
Whom Xiaobo Xia trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Kaiming He
- Yann LeCun
- Yoshua Bengio
- Diederik P. Kingma
- Christian Szegedy
- Ilya Sutskever
- Ross B. Girshick
- Tongliang Liu
Who trusts Xiaobo Xia overall
- Görkem Algan
- Haiyang Zhang
- Tongliang Liu
- Jiaheng Wei
- Hongxin Wei
- Sheng Liu
- Bo Han
- Ilkay Ulusoy
- Ximing Xing
Papers from Xiaobo Xia's perspective
Ordered by how strongly the researchers Xiaobo Xia 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)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- 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
- Are Anchor Points Really Indispensable in Label-Noise Learning? (2019) — 461 citations
- Robust early-learning: Hindering the memorization of noisy labels (2021) — 338 citations
- Part-dependent Label Noise: Towards Instance-dependent Label Noise (2020) — 313 citations