Jialei Wang
Artificial Intelligence · 2014–2018
A researcher in the Science corpus: 11 papers; trusts 163 researchers and is trusted by 50 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 162 citations into it; #4,370 of 35,345 by trust here, #5,682 by citations
- Optimization & Training — 125 citations into it; #1,055 of 2,601 by trust here, #1,537 by citations
- Computational Mechanics — 93 citations into it; #1,910 of 10,001 by trust here, #1,483 by citations
- Statistics and Probability — 68 citations into it
- Computer Vision and Pattern Recognition — 40 citations into it; #14,643 of 21,575 by trust here, #11,083 by citations
- Management Science and Operations Research — 40 citations into it; #2,735 of 11,946 by trust here, #3,825 by citations
- Statistical Learning Theory — 36 citations into it; #837 of 1,038 by trust here, #619 by citations
- Computational Theory and Mathematics — 35 citations into it; #4,174 of 12,182 by trust here, #2,689 by citations
Whom Jialei Wang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ohad Shamir
- Yurii E. Nesterov
- Yuchen Zhang
- Tong Zhang
- Nati Srebro
- Martin J. Wainwright
- John C. Duchi
- Shai Shalev-Shwartz
- Geoffrey E. Hinton
- Alex Krizhevsky
Who trusts Jialei Wang overall
- Mohammad Rostami
- Sebastian U. Stich
- Hanlin Tang
- Ahmed Khaled
- Dong Yin
- Yu Zhang
- Chi Zhang
- Blake E. Woodworth
- Nadia Burkart
- Lijun Zhang
Papers from Jialei Wang's perspective
Ordered by how strongly the researchers Jialei Wang 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
- ImageNet: A large-scale hierarchical image database
- 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
- Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization (2018) — 128 citations
- Memory and Communication Efficient Distributed Stochastic Optimization with Minibatch Prox (2017) — 55 citations
- Distributed Multi-Task Learning (2015) — 79 citations
- Gradient Sparsification for Communication-Efficient Distributed Optimization (2017) — 605 citations
- Warm starting Bayesian optimization (2016) — 74 citations
- Multi-Information Source Optimization (2016) — 230 citations
- Efficient Distributed Learning with Sparsity (2016) — 178 citations
- A General Distributed Dual Coordinate Optimization Framework for Regularized Loss Minimization (2016) — 22 citations
- Distributed Multi-Task Learning with Shared Representation (2016) — 23 citations
- Trading Interpretability for Accuracy: Oblique Treed Sparse Additive Models (2015) — 49 citations
- A Consistent Estimator of the Expected Gradient Outerproduct (2014) — 26 citations