P. Lu

Optimization & Training · with Byrd · 1995–1997

A researcher in the Science corpus: 2 papers; trusts 2 researchers and is trusted by 83 researchers here, as inferred from the citation graph.

Subfields

Whom P. Lu trusts overall

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

  1. Jorge Nocedal
  2. Richard H. Byrd
  3. Andrew R. Conn

Who trusts P. Lu overall

  1. Jakub Konecný
  2. Leon A. Gatys
  3. Jun-Yan Zhu
  4. Yang Liu
  5. Matthew Richardson
  6. N. Matzke
  7. Chengping Rao
  8. Lu Lu
  9. Michael Hirsch
  10. Y. Xiang

Papers from P. Lu's perspective

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

  1. Representations of quasi-Newton matrices and their use in limited memory methods
  2. Constrained minimization methods
  3. The Conjugate Gradient Method and Trust Regions in Large Scale Optimization
  4. On the limited memory BFGS method for large scale optimization
  5. Newton-Type Minimization via the Lanczos Method
  6. The solution of nonlinear finite element equations
  7. INEXACT NEWTON METHODS
  8. A trust region method based on interior point techniques for nonlinear programming (Mathematical programming)
  9. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
  10. Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent

Their papers