Heike Trautmann

Artificial Intelligence · 2006–2018

A researcher in the Science corpus: 6 papers; trusts 28 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

Whom Heike Trautmann trusts overall

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

  1. Thomas G. Dietterich
  2. Yaochu Jin
  3. Frank Hutter
  4. Eric R. Ziegel
  5. Olaf Mersmann
  6. Ron Kohavi
  7. Kevin Leyton-Brown
  8. Radford M. Neal
  9. Leo Breiman
  10. M. Stone

Who trusts Heike Trautmann overall

  1. Bernd Bischl
  2. Pascal Kerschke
  3. Jakub Kudela
  4. Hussain Alibrahim

Papers from Heike Trautmann's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. The Elements of Statistical Learning
  3. Efficient Global Optimization of Expensive Black-Box Functions
  4. Gradient-based learning applied to document recognition
  5. The Nature of Statistical Learning Theory
  6. Pattern Recognition and Machine Learning
  7. Learning Multiple Layers of Features from Tiny Images
  8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  9. Sequential Model-Based Optimization for General Algorithm Configuration
  10. Classification and regression trees

Their papers