Hoyt A. Koepke

Artificial Intelligence · 2015

A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

Whom Hoyt A. Koepke trusts

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

  1. Peter Richtárik (in Artificial Intelligence)
  2. Dimitri P. Bertsekas (in Optimization & Training)
  3. S. Omohundro (in Algorithms & Complexity)
  4. Martin Takác (in Artificial Intelligence)
  5. Mark W. Schmidt (in Optimization & Training)
  6. Olivier Fercoq (in Artificial Intelligence)
  7. A. S. Lewis (in Artificial Intelligence)
  8. D. Leventhal (in Artificial Intelligence)

Who trusts Hoyt A. Koepke

  1. Martin Jaggi (in Artificial Intelligence)
  2. Sebastian U. Stich (in Artificial Intelligence)
  3. Anant Raj (in Artificial Intelligence)

Papers from Hoyt A. Koepke's perspective

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

  1. Nonlinear Programming
  2. Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function
  3. A dual coordinate descent method for large-scale linear SVM
  4. Coordinate descent algorithms for lasso penalized regression
  5. Randomized Methods for Linear Constraints: Convergence Rates and Conditioning (Mathematics of Operations Research)
  6. Error bounds and convergence analysis of feasible descent methods: a general approach
  7. Inducing Features of Random Fields
  8. A coordinate gradient descent method for nonsmooth separable minimization
  9. Learning with Local and Global Consistency
  10. Gaussian Markov Random Fields: Theory and Applications

Their papers