Yihao Feng
Artificial Intelligence · 2016–2023
A researcher in the Science corpus: 7 papers; trusts 179 researchers and is trusted by 18 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 158 citations into it; #17,383 of 35,345 by trust here, #14,438 by citations
- Reinforcement Learning — 97 citations into it; #1,256 of 2,242 by trust here, #1,501 by citations
- Computer Vision and Pattern Recognition — 53 citations into it
- Statistics and Probability — 36 citations into it
- Management Science and Operations Research — 27 citations into it
- Optimization & Training — 26 citations into it
- Probabilistic & Bayesian Methods — 26 citations into it; #624 of 1,525 by trust here, #1,198 by citations
- Evaluation & Benchmarks — 23 citations into it
Whom Yihao Feng trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Richard S. Sutton
- Diederik P. Kingma
- Geoffrey E. Hinton
- Dimitri P. Bertsekas
- Alex Krizhevsky
- Yoshua Bengio
- Michael I. Jordan
- Martin L. Puterman
- Max Welling
- Kaiming He
Who trusts Yihao Feng overall
- Ziyang Tang
- Jiaxin Shi
- Nan Jiang
- Ofir Nachum
- Yingzhen Li
- Jun Zhu
- Scott Fujimoto
- Paria Rashidinejad
- Jiawei Huang
- Chao Ma
Papers from Yihao Feng's perspective
Ordered by how strongly the researchers Yihao Feng 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- 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
- Doubly Robust Bias Reduction in Infinite Horizon Off-Policy Estimation (2019) — 72 citations
- A Kernel Loss for Solving the Bellman Equation (2019) — 75 citations
- LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning (2023) — 1,206 citations
- Incremental Few-shot Text Classification with Multi-round New Classes: Formulation, Dataset and System (2021) — 54 citations
- Action-dependent Control Variates for Policy Optimization via Stein Identity (2018) — 52 citations
- Action-depedent Control Variates for Policy Optimization via Stein's Identity (2017) — 57 citations
- Two Methods for Wild Variational Inference (2016) — 19 citations