Weizhang Liang

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 6 citations into it

Whom Weizhang Liang trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Yoonsuh Jung
2. Tianqi Chen
3. Guolin Ke
4. Carlos Guestrin

Who trusts Weizhang Liang overall

1. Ibomoiye Domor Mienye
2. Yanxia Sun

Papers from Weizhang Liang's perspective

Ordered by how strongly the researchers Weizhang Liang trusts endorse each paper. Same corpus, a different order for every researcher.

1. XGBoost: A Scalable Tree Boosting System
2. LightGBM: A Highly Efficient Gradient Boosting Decision Tree
3. Multiple predicting K-fold cross-validation for model selection
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. ImageNet classification with deep convolutional neural networks
6. Gradient-based learning applied to document recognition
7. Greedy function approximation: A gradient boosting machine.
8. Learning Multiple Layers of Features from Tiny Images
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Predicting Hard Rock Pillar Stability Using GBDT, XGBoost, and LightGBM Algorithms (2020) — 455 citations