Haesun Park

Knowledge Discovery and Data Mining · with Papalexakis · 2018

A researcher in the Science corpus: 1 paper; trusts 0 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Whom Haesun Park trusts overall

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

  1. Jingu Kim
  2. Joyce Ho

Papers from Haesun Park's perspective

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

  1. Learning the parts of objects by non-negative matrix factorization
  2. Multi-Way Analysis: Applications in the Chemical Sciences
  3. Efficient MATLAB Computations with Sparse and Factored Tensors (SIAM Journal on Scientific Computing)
  4. Fast Local Algorithms for Large Scale Nonnegative Matrix and Tensor Factorizations (IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences)
  5. Orthogonal nonnegative matrix t-factorizations for clustering (Knowledge Discovery and Data Mining)
  6. PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene–disease associations
  7. The Expression of a Tensor or a Polyadic as a Sum of Products
  8. Clinical phenotyping in selected national networks: demonstrating the need for high-throughput, portable, and computational methods
  9. Analysis of individual differences in multidimensional scaling via an n-way generalization of “Eckart-Young” decomposition
  10. Fast Nonnegative Matrix Factorization: An Active-Set-Like Method and Comparisons (SIAM Journal on Scientific Computing)

Their papers