Mark Schwabacher

Artificial Intelligence · 2003–2005

A researcher in the Science corpus: 2 papers; trusts 5 researchers and is trusted by 35 researchers here, as inferred from the citation graph.

Subfields

Whom Mark Schwabacher trusts overall

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

  1. Fabrizio Angiulli
  2. Raymond T. Ng
  3. Charles M. Bishop
  4. Clara Pizzuti

Who trusts Mark Schwabacher overall

  1. Gregory W. Vogl
  2. Chao Hu
  3. Fei Tony Liu
  4. Charu C. Aggarwal
  5. Tomás Pevný
  6. B. Weiss
  7. Byeng Dong Youn
  8. Arthur Zimek
  9. Jong-Ho Shin
  10. Hongzhi Wang

Papers from Mark Schwabacher's perspective

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

  1. Multidimensional binary search trees used for associative searching
  2. Distance-based outliers: algorithms and applications (The VLDB journal)
  3. LOF: identifying density-based local outliers
  4. Fast Outlier Detection in High Dimensional Spaces (European Conference on Principles of Data Mining and Knowledge Discovery)
  5. BIRCH: an efficient data clustering method for very large databases
  6. The X-tree : An Index Structure for High-Dimensional Data (Very Large Data Bases Conference)
  7. When Is ''Nearest Neighbor'' Meaningful?
  8. Outlier mining in large high-dimensional data sets (IEEE Transactions on Knowledge and Data Engineering)
  9. Efficient algorithms for mining outliers from large data sets (ACM SIGMOD Conference)
  10. A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise

Their papers