Mingmin Zhao
Artificial Intelligence · with Hajinezhad · 2017
A researcher in the Science corpus: 1 paper; trusts 18 researchers and is trusted by 6 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 12 citations into it; #18,402 of 35,345 by trust here, #28,481 by citations
- Computational Mechanics — 11 citations into it; #4,910 of 10,001 by trust here, #7,501 by citations
- Computer Networks and Communications — 9 citations into it; #4,488 of 9,886 by trust here, #7,492 by citations
- Optimization & Training — 7 citations into it
Whom Mingmin Zhao trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Dimitri P. Bertsekas
- M. Powell
- Angelia Nedić
- Mingyi Hong
- Rie Johnson
- Mark W. Schmidt
- Zeyuan Allen-Zhu
- D. P. Palomar
- Francis R. Bach
- Aaron Defazio
Who trusts Mingmin Zhao overall
Papers from Mingmin Zhao's perspective
Ordered by how strongly the researchers Mingmin Zhao 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)
- Accelerating Stochastic Gradient Descent using Predictive Variance Reduction
- Gradient-based learning applied to document recognition
- Learning Multiple Layers of Features from Tiny Images
- SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Minimizing finite sums with the stochastic average gradient