BibSLEIGH — Ian

Travelled to:

1 × Australia
1 × France
10 × USA
2 × China

Collaborated with:

X.Wang W.Fan J.Ye B.Qian S.S.Ravi M.Ester R.Chattopadhyay S.Panchanathan A.Gress ∅ Z.Qi G.Paul S.Gilpin R.Ge W.Jin A.Grover A.Satyanarayana G.K.Tayi F.Wang P.Zhang C.Kuo P.B.Walker O.T.Carmichael S.Yang Q.Sun S.Ji P.Wonka Z.Wang M.S.Hossain S.Tadepalli L.T.Watson R.F.Helm N.Ramakrishnan

Talks about:

cluster (10) data (4) constraint (3) framework (3) flexibl (3) effici (3) constrain (2) approach (2) select (2) applic (2)

Person: Ian Davidson

DBLP: Davidson:Ian

Contributed to:

2015

2014

2013

2012

2011

2010

2009

2007

2006

2004

Wrote 19 papers:

KDD-2015-KuoWWCYD #graph #multi #segmentation: Unified and Contrasting Cuts in Multiple Graphs: Application to Medical Imaging Segmentation (CTK, XW, PBW, OTC, JY, ID), pp. 617–626.
KDD-2015-YangSJWDY #learning #visual notation: Structural Graphical Lasso for Learning Mouse Brain Connectivity (SY, QS, SJ, PW, ID, JY), pp. 1385–1394.
CIKM-2014-GressD #flexibility #framework #semistructured data: A Flexible Framework for Projecting Heterogeneous Data (AG, ID), pp. 1169–1178.
KDD-2014-WangZQWD #multi #predict #risk management: Clinical risk prediction with multilinear sparse logistic regression (FW, PZ, BQ, XW, ID), pp. 145–154.
CIKM-2013-GilpinQD #clustering #dataset #performance #scalability: Efficient hierarchical clustering of large high dimensional datasets (SG, BQ, ID), pp. 1371–1380.
ICML-c3-2013-ChattopadhyayFDPY #learning: Joint Transfer and Batch-mode Active Learning (RC, WF, ID, SP, JY), pp. 253–261.
CIKM-2012-WangQD #automation #clustering #documentation #using: Improving document clustering using automated machine translation (XW, BQ, ID), pp. 645–653.
KDD-2012-ChattopadhyayWFDPY #probability: Batch mode active sampling based on marginal probability distribution matching (RC, ZW, WF, ID, SP, JY), pp. 741–749.
KDD-2012-Davidson #clustering #comprehension #constraints: Two approaches to understanding when constraints help clustering (ID), pp. 1312–1320.
KDD-2011-ChattopadhyayYPFD #adaptation #detection #multi: Multi-source domain adaptation and its application to early detection of fatigue (RC, JY, SP, WF, ID), pp. 717–725.
KDD-2010-HossainTWDHR #clustering: Unifying dependent clustering and disparate clustering for non-homogeneous data (MSH, ST, LTW, ID, RFH, NR), pp. 593–602.
KDD-2010-WangD #clustering #flexibility: Flexible constrained spectral clustering (XW, ID), pp. 563–572.
KDD-2009-QiD #clustering #flexibility #framework: A principled and flexible framework for finding alternative clusterings (ZQ, ID), pp. 717–726.
ICML-2007-DavidsonR #clustering #constraints: Intractability and clustering with constraints (ID, SSR), pp. 201–208.
KDD-2007-DavidsonRE #clustering #incremental #performance: Efficient incremental constrained clustering (ID, SSR, ME), pp. 240–249.
KDD-2007-GeEJD #clustering #constraints: Constraint-driven clustering (RG, ME, WJ, ID), pp. 320–329.
KDD-2006-FanD #bias #classification #framework #performance #testing: Reverse testing: an efficient framework to select amongst classifiers under sample selection bias (WF, ID), pp. 147–156.
KDD-2004-DavidsonGST #algorithm #approach #data mining #matrix #mining #quality: A general approach to incorporate data quality matrices into data mining algorithms (ID, AG, AS, GKT), pp. 794–798.
KDD-2004-DavidsonP #image: Locating secret messages in images (ID, GP), pp. 545–550.