Travelled to:1 × Australia
1 × France
1 × Portugal
1 × South Korea
1 × Spain
3 × USA
Collaborated with:B.Pfahringer R.Gavaldà G.Holmes J.Read F.Pérez-Cruz D.Ienco P.Poncelet K.Kutzkov F.Bonchi A.Gionis G.D.F.Morales G.Holmes R.Kirkby H.Kremer P.Kranen T.Jansen T.Seidl
Talks about:stream (9) data (8) evolv (4) frequent (2) effici (2) learn (2) evalu (2) close (2) adapt (2) mine (2)
Person: Albert Bifet
DBLP: Bifet:Albert
Contributed to:
2015
2015201420132013201120092008Wrote 9 papers:
- KDD-2015-BifetMRHP #big data #classification #data type #evaluation #online #performance
- Efficient Online Evaluation of Big Data Stream Classifiers (AB, GDFM, JR, GH, BP), pp. 59–68.
- SAC-2015-ReadPB #data type #learning
- Deep learning in partially-labeled data streams (JR, FPC, AB), pp. 954–959.
- SAC-2014-IencoBPP #category theory #data type #detection #evolution
- Change detection in categorical evolving data streams (DI, AB, BP, PP), pp. 792–797.
- KDD-2013-KutzkovBBG #learning #named
- STRIP: stream learning of influence probabilities (KK, AB, FB, AG), pp. 275–283.
- SAC-2013-BifetPRH #adaptation #classification #data type #performance #probability
- Efficient data stream classification via probabilistic adaptive windows (AB, BP, JR, GH), pp. 801–806.
- KDD-2011-BifetHPG #data type #evolution #graph #mining
- Mining frequent closed graphs on evolving data streams (AB, GH, BP, RG), pp. 591–599.
- KDD-2011-KremerKJSBHP #clustering #data type #effectiveness #evaluation #evolution
- An effective evaluation measure for clustering on evolving data streams (HK, PK, TJ, TS, AB, GH, BP), pp. 868–876.
- KDD-2009-BifetHPKG #data type #evolution
- New ensemble methods for evolving data streams (AB, GH, BP, RK, RG), pp. 139–148.
- KDD-2008-BifetG #adaptation #data type #mining
- Mining adaptively frequent closed unlabeled rooted trees in data streams (AB, RG), pp. 34–42.