Zhong Ming
Artificial Intelligence · 2012–2018
A researcher in the Science corpus: 9 papers; trusts 44 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 90 citations into it
- Information Systems — 75 citations into it; #7,510 of 8,771 by trust here, #3,098 by citations
- Computer Vision and Pattern Recognition — 37 citations into it
- Recommender Systems — 37 citations into it
- Management Science and Operations Research — 23 citations into it; #10,580 of 11,946 by trust here, #4,921 by citations
- Computer Networks and Communications — 17 citations into it
- Electrical and Electronic Engineering — 17 citations into it
- Representation & Self-Supervised Learning — 16 citations into it
Whom Zhong Ming trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yehuda Koren
- Steffen Rendle
- Weike Pan
- Ruslan Salakhutdinov
- Qiang Yang
- Sinno Jialin Pan
- Geoffrey E. Hinton
- Yoshua Bengio
- Santosh Kabbur
- Andriy Mnih
Who trusts Zhong Ming overall
Papers from Zhong Ming's perspective
Ordered by how strongly the researchers Zhong Ming 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)
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- 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
- Transfer Learning for Semisupervised Collaborative Recommendation (2016) — 20 citations
- Compressed knowledge transfer via factorization machine for heterogeneous collaborative recommendation (2015) — 59 citations
- Adaptive Bayesian personalized ranking for heterogeneous implicit feedbacks (2015) — 168 citations
- A review on neural networks with random weights (2018) — 470 citations
- Transfer Learning for Behavior Ranking (2017) — 42 citations
- Privacy Protection for Preventing Data Over-Collection in Smart City (2016) — 310 citations
- Transfer Learning for Heterogeneous One-Class Collaborative Filtering (2016) — 48 citations
- Phase-Change Memory Optimization for Green Cloud with Genetic Algorithm (2015) — 350 citations
- Online optimization for scheduling preemptable tasks on IaaS cloud systems (2012) — 392 citations