Michael D. Muhlbaier

Artificial Intelligence · 2009

A researcher in the Science corpus: 1 paper; trusts 14 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

Whom Michael D. Muhlbaier trusts overall

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

  1. Robert E. Schapire
  2. Leo Breiman
  3. Yoav Freund
  4. J. Kolter
  5. Jeffrey C. Schlimmer
  6. Ludmila I. Kuncheva
  7. W. Street
  8. Nikunj C. Oza
  9. Paul E. Utgoff
  10. M. Maloof

Who trusts Michael D. Muhlbaier overall

  1. Ryan Elwell
  2. Qing Da
  3. Heitor Murilo Gomes
  4. Ali Ayub
  5. Robi Polikar
  6. Yang Yu
  7. Jean Paul Barddal
  8. Alan R. Wagner

Papers from Michael D. Muhlbaier's perspective

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

  1. Bagging Predictors
  2. ImageNet classification with deep convolutional neural networks
  3. Gradient-based learning applied to document recognition
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. The Strength of Weak Learnability
  6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  7. A decision-theoretic generalization of on-line learning and an application to boosting
  8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. Long Short-Term Memory

Their papers