Joshua Hibschman

ACM Symposium on User Interface Software and Technology · 2017

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Whom Joshua Hibschman trusts

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

  1. Yoshua Bengio (in Artificial Intelligence)

Papers from Joshua Hibschman's perspective

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

  1. Rectified Linear Units Improve Restricted Boltzmann Machines
  2. Learning Deep Architectures for AI
  3. ImageNet classification with deep convolutional neural networks
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. Learning visual similarity for product design with convolutional neural networks
  6. Gradient-based learning applied to document recognition
  7. Image-Based Recommendations on Styles and Substitutes
  8. A large-scale hierarchical image database
  9. A search engine for 3D models (TOGS)
  10. Example-centric programming: integrating web search into the development environment (International Conference on Human Factors in Computing Systems)

Their papers