Carsten Binnig

Optimization & Training · 2016–2019

A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Carsten Binnig trusts

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

  1. Frank Hutter (in Optimization & Training)

Papers from Carsten Binnig's perspective

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

  1. Reinforcement Learning: An Introduction
  2. Random Search for Hyper-Parameter Optimization
  3. Scikit-learn: Machine Learning in Python
  4. Neural Architecture Search with Reinforcement Learning
  5. Sequential Model-Based Optimization for General Algorithm Configuration
  6. TensorFlow: A system for large-scale machine learning
  7. Learning to learn by gradient descent by gradient descent
  8. Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting
  9. Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization
  10. Controlling the false discovery rate: a practical and powerful approach to multiple testing

Their papers