Murray Browne

Artificial Intelligence · 2007

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

Whom Murray Browne trusts overall

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

  1. Patrik O. Hoyer
  2. Chih-Jen Lin
  3. Daniel D. Lee
  4. P. Paatero
  5. Andrzej S. Cichocki
  6. Farial Shahnaz
  7. H. Wold

Who trusts Murray Browne overall

  1. Hyunsoo Kim
  2. Andrzej S. Cichocki
  3. Haesun Park
  4. Nicolas Gillis
  5. Jingu Kim
  6. Yangyang Xu
  7. Leilani H. Gilpin
  8. Sen Jia
  9. Yu-Xiong Wang
  10. Renaud Gaujoux

Papers from Murray Browne's perspective

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

  1. Learning the parts of objects by non-negative matrix factorization
  2. Algorithms for Non-negative Matrix Factorization
  3. Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values†
  4. Non-negative sparse coding
  5. Non-negative Matrix Factorization with Sparseness Constraints (Journal of machine learning research)
  6. Projected Gradient Methods for Nonnegative Matrix Factorization
  7. On the convergence of the block nonlinear Gauss-Seidel method under convex constraints (Operations Research Letters)
  8. Generalized Nonnegative Matrix Approximations with Bregman Divergences (Neural Information Processing Systems)
  9. Text Mining Using Non-Negative Matrix Factorizations (SDM)
  10. On reduced rank nonnegative matrix factorization for symmetric nonnegative matrices

Their papers