Travelled to:1 × Germany
1 × Hungary
1 × Portugal
1 × Spain
3 × USA
Collaborated with:L.D.Raedt R.Brijder J.Struyf J.Ramon C.Vens B.Verstrynge D.Page A.Srinivasan S.Dzeroski T.Calders É.Fromont B.Goethals A.Prado C.Robardet B.Bogaerts M.Bruynooghe B.d.Cat S.D.Pooter M.Denecker A.Labarre S.Verwer
Talks about:cluster (3) learn (3) tree (3) induct (2) mine (2) character (1) algorithm (1) supervis (1) subgraph (1) reinforc (1)
Person: Hendrik Blockeel
DBLP: Blockeel:Hendrik
Contributed to:
2013
2012
2011
2008
200520011998Wrote 8 papers:
- KDIR-KMIS-2013-VensVB #clustering
- Semi-supervised Clustering with Example Clusters (CV, BV, HB), pp. 45–51.
- ICLP-2012-BlockeelBBCP #data mining #machine learning #mining #modelling #problem
- Modeling Machine Learning and Data Mining Problems with FO(·) (HB, BB, MB, BdC, SDP, MD, AL, JR, SV), pp. 14–25.
- LATA-2011-BrijderB
- Characterizing Compressibility of Disjoint Subgraphs with NLC Grammars (RB, HB), pp. 167–178.
- KDD-2008-BlockeelCFGPR #database #induction #mining #prototype
- An inductive database prototype based on virtual mining views (HB, TC, ÉF, BG, AP, CR), pp. 1061–1064.
- ICML-2005-BlockeelPS #learning #multi
- Multi-instance tree learning (HB, DP, AS), pp. 57–64.
- ICML-2001-BlockeelS #algorithm #performance
- Efficient algorithms for decision tree cross-validation (HB, JS), pp. 11–18.
- ICML-1998-BlockeelRR #clustering #induction #top-down
- Top-Down Induction of Clustering Trees (HB, LDR, JR), pp. 55–63.
- ICML-1998-DzeroskiRB #learning #relational
- Relational Reinforcement Learning (SD, LDR, HB), pp. 136–143.