Travelled to:1 × Spain
4 × USA
Collaborated with:U.M.Fayyad C.Reina O.L.Mangasarian C.Yang N.Rothleder J.Shanmugasundaram
Talks about:cluster (4) algorithm (2) databas (2) dimens (2) refin (2) initi (2) larg (2) data (2) enterpris (1) discoveri (1)
Person: Paul S. Bradley
DBLP: Bradley:Paul_S=
Contributed to:
20012001
20001999
19981998Wrote 8 papers:
- KDD-2001-YangFB #performance
- Efficient discovery of error-tolerant frequent itemsets in high dimensions (CY, UMF, PSB), pp. 194–203.
- KDD-T-2001-FayyadRB #data mining #enterprise #mining
- E-business enterprise data mining (UMF, NR, PSB), pp. 1–85.
- ICPR-v2-2000-BradleyRF #clustering #database #modelling #scalability #using
- Clustering Very Large Databases Using EM Mixture Models (PSB, CR, UMF), pp. 2076–2080.
- KDD-1999-ShanmugasundaramFB #approximate #query
- Compressed Data Cubes for OLAP Aggregate Query Approximation on Continuous Dimensions (JS, UMF, PSB), pp. 223–232.
- ICML-1998-BradleyF #clustering
- Refining Initial Points for K-Means Clustering (PSB, UMF), pp. 91–99.
- ICML-1998-BradleyM #feature model
- Feature Selection via Concave Minimization and Support Vector Machines (PSB, OLM), pp. 82–90.
- KDD-1998-BradleyFR #algorithm #clustering #database #scalability
- Scaling Clustering Algorithms to Large Databases (PSB, UMF, CR), pp. 9–15.
- KDD-1998-FayyadRB #algorithm #clustering #refinement
- Initialization of Iterative Refinement Clustering Algorithms (UMF, CR, PSB), pp. 194–198.