BibSLEIGH — Lise

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: Getoor:Lise

Facilitated 2 volumes:

Contributed to:

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2004

2003

2001

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.