Hao Yu

Optimization & Training · IEEE Transactions on Neural Networks · 2010–2012

A researcher in the Science corpus: 3 papers; trusts 4 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

Whom Hao Yu trusts overall

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

  1. Bogdan M. Wilamowski
  2. G. Huang
  3. David E. Rumelhart
  4. Paramasivan Saratchandran
  5. Geoffrey E. Hinton

Who trusts Hao Yu overall

  1. David K. Hunter
  2. K. Sheela
  3. Man Zhou
  4. Zhi Liu
  5. Michael S. Pukish III
  6. Bogdan M. Wilamowski

Papers from Hao Yu's perspective

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

  1. Learning representations by back-propagating errors
  2. UCI Repository of machine learning databases
  3. An efficient sequential learning algorithm for growing and pruning RBF (GAP-RBF) networks (IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics))
  4. Universal Approximation Using Radial-Basis-Function Networks
  5. A direct adaptive method for faster backpropagation learning: the RPROP algorithm
  6. Improved Computation for Levenberg–Marquardt Training (IEEE Transactions on Neural Networks)
  7. Geometrical and Statistical Properties of Systems of Linear Inequalities with Applications in Pattern Recognition
  8. Learning Speaker-Specific Characteristics With a Deep Neural Architecture
  9. Neural Network Applications in Power Electronics and Motor Drives—An Introduction and Perspective (IEEE transactions on industrial electronics (1982. Print))
  10. State-of-Charge Estimation for Lithium-Ion Batteries Using Neural Networks and EKF (IEEE transactions on industrial electronics (1982. Print))

Their papers