Simon Hawkins

Artificial Intelligence · 2002

A researcher in the Science corpus: 2 papers; trusts 7 researchers and is trusted by 17 researchers here, as inferred from the citation graph.

Subfields

Whom Simon Hawkins trusts overall

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

  1. Robert Hecht-Nielsen
  2. David H. Ackley
  3. Kenji Yamanishi
  4. Tian Zhang
  5. Martin Ester
  6. Raymond T. Ng
  7. Geoffrey E. Hinton
  8. Hans-Peter Kriegel
  9. Jun'ichi Takeuchi
  10. Raghu Ramakrishnan

Who trusts Simon Hawkins overall

  1. Heiko Paulheim
  2. Lukas Ruff
  3. Mayu Sakurada
  4. Jacopo Castellini
  5. Varun Chandola
  6. Yuntao Liu
  7. Guansong Pang
  8. Clifton Phua
  9. Charu C. Aggarwal
  10. Vikash Sehwag

Papers from Simon Hawkins's perspective

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

  1. A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise
  2. BIRCH: an efficient data clustering method for very large databases
  3. A Learning Algorithm for Boltzmann Machines
  4. UCI Repository of machine learning databases
  5. On-Line Unsupervised Outlier Detection Using Finite Mixtures with Discounting Learning Algorithms (Knowledge Discovery and Data Mining)
  6. Efficient algorithms for mining outliers from large data sets (ACM SIGMOD Conference)
  7. Replicator neural networks for universal optimal source coding.
  8. Mining top-n local outliers in large databases (Knowledge Discovery and Data Mining)
  9. LOF: identifying density-based local outliers
  10. Robust Regression and Outlier Detection (Wiley Series in Probability and Statistics)

Their papers