La Creis Kidd

Genetics · 2016

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

Whom La Creis Kidd trusts

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

  1. Wolfgang Banzhaf (in Evolutionary Computation)
  2. Jason H. Moore (in Genetics)

Who trusts La Creis Kidd

  1. Davide Chicco (in Artificial Intelligence)
  2. Marc-André Zöller (in Artificial Intelligence)
  3. Marco F. Huber (in Artificial Intelligence)

Papers from La Creis Kidd's perspective

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

  1. Practical Bayesian Optimization of Machine Learning Algorithms
  2. Random Search for Hyper-Parameter Optimization
  3. A fast and elitist multiobjective genetic algorithm: NSGA-II
  4. GAMETES: a fast, direct algorithm for generating pure, strict, epistatic models with random architectures
  5. Spatially Uniform ReliefF (SURF) for computationally-efficient filtering of gene-gene interactions
  6. DEAP: evolutionary algorithms made easy
  7. Scikit-learn: Machine Learning in Python
  8. The Design of Innovation: Lessons from and for Competent Genetic Algorithms
  9. Multi-objective optimization using genetic algorithms: A tutorial
  10. A genetic programming approach to automated software repair

Their papers