Nicole A. Lavender

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 Nicole A. Lavender trusts overall

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

  1. Wolfgang Banzhaf

Who trusts Nicole A. Lavender overall

  1. Davide Chicco
  2. Marc-André Zöller
  3. Marco F. Huber

Papers from Nicole A. Lavender's perspective

Ordered by how strongly the researchers Nicole A. Lavender 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. Scikit-learn: Machine Learning in Python
  5. GAMETES: a fast, direct algorithm for generating pure, strict, epistatic models with random architectures
  6. Spatially Uniform ReliefF (SURF) for computationally-efficient filtering of gene-gene interactions
  7. DEAP: evolutionary algorithms made easy
  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