Michael Papamichael

Electrical and Electronic Engineering · 2010–2018

A researcher in the Science corpus: 4 papers; trusts 3 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

Whom Michael Papamichael trusts overall

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

  1. Onur Mutlu
  2. Thomas Moscibroda
  3. Yoongu Kim
  4. Scott Rixner

Who trusts Michael Papamichael overall

  1. Onur Mutlu
  2. Yoongu Kim
  3. Sai Prashanth Muralidhara

Papers from Michael Papamichael's perspective

Ordered by how strongly the researchers Michael Papamichael 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. Long Short-Term Memory
  4. Caffe: Convolutional Architecture for Fast Feature Embedding
  5. Learning both Weights and Connections for Efficient Neural Network
  6. Balancing thoughput and fairness in SMT processors (2001 IEEE International Symposium on Performance Analysis of Systems and Software. ISPASS.)
  7. Deep Compression: Compressing Deep Neural Network with Pruning, Trained Quantization and Huffman Coding
  8. XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
  9. Memory access scheduling (Proceedings of 27th International Symposium on Computer Architecture (IEEE Cat. No.RS00201))
  10. Gradient-based learning applied to document recognition

Their papers