Peter Milder

Computer Vision and Pattern Recognition · 2016–2017

A researcher in the Science corpus: 3 papers; trusts 141 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 49 citations into it; #10,477 of 21,575 by trust here, #8,831 by citations
• Electrical and Electronic Engineering — 30 citations into it; #4,897 of 16,539 by trust here, #6,291 by citations
• Artificial Intelligence — 19 citations into it; #16,513 of 35,345 by trust here, #12,761 by citations
• Hardware and Architecture — 18 citations into it
• ML Systems & Hardware — 13 citations into it
• Efficiency & Compression — 10 citations into it; #765 of 1,264 by trust here, #925 by citations
• Model Architectures — 9 citations into it

Whom Peter Milder trusts overall

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

1. Alex Krizhevsky
2. Karen Simonyan
3. Geoffrey E. Hinton
4. Ilya Sutskever
5. Andrew Zisserman
6. Clément Farabet
7. Christian Szegedy
8. Yann LeCun
9. Srimat T. Chakradhar
10. Ronan Collobert

Who trusts Peter Milder overall

1. Sparsh Mittal
2. Yongming Shen

Papers from Peter Milder's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Gradient-based learning applied to document recognition
4. Going deeper with convolutions
5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
6. ImageNet Large Scale Visual Recognition Challenge
7. Long Short-Term Memory
8. ImageNet: A large-scale hierarchical image database
9. Attention is All you Need (Neural Information Processing Systems)
10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers

• Maximizing CNN accelerator efficiency through resource partitioning (2016) — 336 citations
• Fused-layer CNN accelerators (2016) — 668 citations
• Escher: A CNN Accelerator with Flexible Buffering to Minimize Off-Chip Transfer (2017) — 106 citations