Dae-ki Cho

Statistics and Probability · 2018

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

Subfields

Whom Dae-ki Cho trusts

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

  1. Peter Filzmoser (in Statistics and Probability)

Papers from Dae-ki Cho's perspective

Ordered by how strongly the researchers Dae-ki Cho trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  2. Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion
  3. TensorFlow: A system for large-scale machine learning
  4. Adaptive Mixtures of Local Experts
  5. An Introduction to Variational Methods for Graphical Models
  6. Neural Variational Inference and Learning in Belief Networks
  7. Anomaly detection: A survey
  8. Unsupervised Deep Embedding for Clustering Analysis
  9. A comparative study of RNN for outlier detection in data mining (IEEE International Conference on Data Mining. Proceedings)
  10. A survey on unsupervised outlier detection in high‐dimensional numerical data (Statistical analysis and data mining)

Their papers