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Travelled to:
1 × Australia
1 × Austria
1 × China
1 × Greece
1 × Israel
1 × Portugal
12 × USA
3 × France
Collaborated with:
A.Machanavajjhala A.Deshpande P.Sen J.R.Foulds B.Huang L.Mihalkova M.Bilgic B.London G.Namata K.Lerman T.Rekatsinas Q.Lu S.Fakhraei S.H.Kumar S.Kok A.Plangprasopchok E.Zheleva H.Sharara K.Schnaitter N.Polyzotis O.Udrea R.J.Miller I.Bhattacharya L.Licamele S.H.Bach J.L.Boyd-Graber M.V.S.Shashanka B.Taskar Y.Zhu X.Yan C.Moore W.E.Moustafa H.Miao B.Staats B.Shneiderman S.Minton C.A.Knoblock N.Friedman D.Koller B.Taskar X.He Y.Liu P.Kouki M.Eirinaki G.Piatetsky-Shapiro R.Grossman C.Djeraba R.Feldman M.J.Zaki N.Ramakrishnan P.Butler S.Muthiah N.Self R.P.Khandpur P.Saraf W.Wang J.Cadena A.Vullikanti G.Korkmaz C.J.Kuhlman A.Marathe L.Zhao T.Hua F.Chen C.Lu A.Srinivasan K.Trinh G.Katz A.Doyle C.Ackermann I.Zavorin J.Ford K.M.Summers Y.Fayed J.Arredondo D.Gupta D.Mares
Talks about:
network (9) model (7) probabilist (6) structur (6) learn (6) topic (5) data (5) collect (4) interact (3) resolut (3)

Person: Lise Getoor

DBLP DBLP: Getoor:Lise

Facilitated 2 volumes:

ICML 2011Ed
KDD 2003Ed

Contributed to:

ICML 20152015
KDD 20152015
RecSys 20152015
KDD 20142014
ICML c3 20132013
KDD 20132013
SIGMOD 20132013
SIGMOD 20122012
VLDB 20122012
KDD 20112011
SIGMOD 20112011
ICML 20102010
KDD 20102010
VLDB 20102010
KDD 20092009
VLDB 20092009
KDD 20082008
VLDB 20082008
CIKM 20072007
SIGMOD 20072007
ICML 20062006
KDD 20062006
SIGMOD 20042004
ICML 20032003
ICML 20012001

Wrote 31 papers:

ICML-2015-BachHBG #learning #performance
Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs (SHB, BH, JLBG, LG), pp. 381–390.
ICML-2015-FouldsKG #framework #modelling #network #probability #programming #topic
Latent Topic Networks: A Versatile Probabilistic Programming Framework for Topic Models (JRF, SHK, LG), pp. 777–786.
ICML-2015-HeRFGL #modelling #named #network #topic
HawkesTopic: A Joint Model for Network Inference and Topic Modeling from Text-Based Cascades (XH, TR, JRF, LG, YL), pp. 871–880.
ICML-2015-LondonHG #approximate #learning
The Benefits of Learning with Strongly Convex Approximate Inference (BL, BH, LG), pp. 410–418.
KDD-2015-FakhraeiFSG #detection #evolution #multi #network #social
Collective Spammer Detection in Evolving Multi-Relational Social Networks (SF, JRF, MVSS, LG), pp. 1769–1778.
RecSys-2015-KoukiFFEG #flexibility #framework #hybrid #named #probability #recommendation
HyPER: A Flexible and Extensible Probabilistic Framework for Hybrid Recommender Systems (PK, SF, JRF, ME, LG), pp. 99–106.
KDD-2014-RamakrishnanBMSKSWCVKKMZHCLHSTGKDAZFSFAGM #open source #using
“Beating the news” with EMBERS: forecasting civil unrest using open source indicators (NR, PB, SM, NS, RPK, PS, WW, JC, AV, GK, CJK, AM, LZ, TH, FC, CTL, BH, AS, KT, LG, GK, AD, CA, IZ, JF, KMS, YF, JA, DG, DM), pp. 1799–1808.
ICML-c3-2013-LondonHTG #predict
Collective Stability in Structured Prediction: Generalization from One Example (BL, BH, BT, LG), pp. 828–836.
KDD-2013-GetoorM #big data
Entity resolution for big data (LG, AM), p. 1527.
KDD-2013-GetoorM13a #network
Network sampling (LG, AM), p. 1528.
KDD-2013-ZhuYGM #analysis #modelling #scalability #topic
Scalable text and link analysis with mixed-topic link models (YZ, XY, LG, CM), pp. 473–481.
SIGMOD-2013-MoustafaMDG #analysis #declarative #interactive #named #network
GRDB: a system for declarative and interactive analysis of noisy information networks (WEM, HM, AD, LG), pp. 1085–1088.
SIGMOD-2012-RekatsinasDG #database #probability
Local structure and determinism in probabilistic databases (TR, AD, LG), pp. 373–384.
VLDB-2012-GetoorM #challenge
Entity Resolution: Theory, Practice & Open Challenges (LG, AM), pp. 2018–2019.
KDD-2011-NamataKG #graph #identification
Collective graph identification (GN, SK, LG), pp. 87–95.
SIGMOD-2011-GetoorM #learning #modelling #relational #statistics
Learning statistical models from relational data (LG, LM), pp. 1195–1198.
ICML-2010-BilgicMG #learning
Active Learning for Networked Data (MB, LM, LG), pp. 79–86.
KDD-2010-PlangprasopchokLG #folksonomy #metadata
Growing a tree in the forest: constructing folksonomies by integrating structured metadata (AP, KL, LG), pp. 949–958.
VLDB-2010-SenDG #database #evaluation #probability #query
Read-Once Functions and Query Evaluation in Probabilistic Databases (PS, AD, LG), pp. 1068–1079.
KDD-2009-ZhelevaSG #co-evolution #network #social
Co-evolution of social and affiliation networks (EZ, HS, LG), pp. 1007–1016.
VLDB-2009-SchnaitterPG #analysis #design #interactive #modelling #physics
Index Interactions in Physical Design Tuning: Modeling, Analysis, and Applications (KS, NP, LG), pp. 1234–1245.
KDD-2008-BilgicG #classification #effectiveness
Effective label acquisition for collective classification (MB, LG), pp. 43–51.
VLDB-2008-SenDG #correlation #database #probability
Exploiting shared correlations in probabilistic databases (PS, AD, LG), pp. 809–820.
CIKM-2007-NamataSGS #approach #interactive #network #visualisation
A dual-view approach to interactive network visualization (GN, BS, LG, BS), pp. 939–942.
SIGMOD-2007-UdreaGM #integration #ontology
Leveraging data and structure in ontology integration (OU, LG, RJM), pp. 449–460.
ICML-2006-SenG #learning #markov #network
Cost-sensitive learning with conditional Markov networks (PS, LG), pp. 801–808.
KDD-2006-BhattacharyaGL
Query-time entity resolution (IB, LG, LL), pp. 529–534.
KDD-2006-Piatetsky-ShapiroGDFGZ #challenge #data mining #mining #question
Is there a grand challenge or X-prize for data mining? (GPS, RG, CD, RF, LG, MJZ), pp. 954–956.
SIGMOD-2004-LermanGMK #automation #segmentation #using #web
Using the Structure of Web Sites for Automatic Segmentation of Tables (KL, LG, SM, CAK), pp. 119–130.
ICML-2003-LuG #classification
Link-based Classification (QL, LG), pp. 496–503.
ICML-2001-GetoorFKT #learning #modelling #probability #relational
Learning Probabilistic Models of Relational Structure (LG, NF, DK, BT), pp. 170–177.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
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