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Author
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Ackermann, Chris
Aggarwal, Charu
Amantullah, Brian
Ariel, Fuxman
Arredondo, Jaime
Arredondo, Jaime
Arti, Ramesh
Augustine, Eriq
Babaki, Behrouz
Bach, Stephen H.
Bach, Stephen
Barash, Vladimir
Beard, Mitchell
Bengio, Yoshua
Bert, Huang
Bhattacharya, Indrajit
Bhattacharya, Indrajit
Bilgic, Mustafa
Bilgic, Mustafa
Blake, Brian
Blondeel, Marjon
Borgatti, Steve
Boyd-Graber, Jordan
Bradley, Skaggs
Broecheler, Matthias
Broecheler, Matthias
Brownstein, John
Brownstein, John
Butler, Patrick
Cadena, Jose
Carlson, Bjorn
Carstea, Eugene
Chajewska, Ursulza
Chang, Johnnie
Chen, Daozheng
Chen, Yunfei
Chen, Robert
Choi, Jonghyun
Cohen, William
Cook, Diane
Daozheng, Chen
Daume, Hal
David, Jacobs
Davis, Larry
Davis, Larry
De Cock, Martine
Deshpande, Amol
Deshpande, Amol
Dhanya, Sridhar
Diehl, Christopher
Dietterich, Thomas
Djeraba, Chabane
Domingos, Pedro
Dong, Xin Luna
Dong, Luna
Dong, Xin Luna
Doppa, Janardhan
Doyle, Andy
Dzeroski, Saso
Eirinaki, Magdalini
Eliassi-Rad, Tina
Elsayed, Tamer
Embar, Varun
Eric, Norris
Fakhraei, Shobeir
Fakhraei, Shobeir
Faloutsos, Christos
Farnadi, Golnoosh
Fayed, Youssef
Feldman, Ronen
Ford, Jim
Foulds, James
Foulds, James
Friedman, Nir
Friedman, Nir
Friedman, Mark
Fromherz, Markus
Gallagher, Brian
Gazen, Bora C.
Getoor, Lise
Ghosh, Saurav
Ghosh, Saurav
Golbeck, Jennifer
Golbeck, Jennifer
Goldwasser, Dan
Goldwasser, Dan
Grant, John
Grossman, Robert
Grycner, Adam
Grycner, Adam
Guiver, John
Gupta, Dipak
Gupta, Dipak
Haidarian-Shahri, Hamid
Halgin, Daniel
Han, Jiawei
He, Xinran
Healy, Patrick
Holder, Lawrence
Hollis, Victoria
Hossam, Sharara
Huang, Bert
Huang, Bert
Hung, Edward
Hwang, Heasoo
III, Hal Daume
Islamaj, Rezarta
Islamaj, Rezarta
Isley, Steve
Jacobs, David
Jaebong, Yoo
Janet, Mann
Jay, Pujara
Jihie, Kim
Jr., Nick Short
Kang, Jeonhyung
Kang, Hyunmo
Katz, Graham
Katz, Graham
Kayali, Moe
Khamis, Sameh
Khandpur, Rupinder
Kim, Sungchul
Kimmig, Angelika
Kimmig, Angelika
Kini, Nikhil
Knoblock, Craig
Koehly, Laura
Koehly, Laura
Koh, Eunyee
Kok, Stanley
Kolcz, Alek
Koller, Daphne
Koller, Daphne
Korkmaz, Gizem
Kouki, Pigi
Kouki, Pigi
Kuhlman, Christopher
Kumar, Shachi
Kumar, Shachi
Kuter, Ugur
Lansky, Amy
Lauw, Hady
Lavedan, Christian
Lavrac, Nada
Lerman, Kristina
Licamele, Louis
Lilyana, Mihalkova
Lisa, Singh
Liu, Xiangyang
Liu, Huan
Liu, Yan
London, Ben
London, Ben
Lu, Qing
Machanavajjhala, Ashwin
Machanavajjhala, Ashwin
Mack, Kendra
Macskassy, Sofus
Mann, Janet
Marathe, Achla
Marcum, Christopher
Marcum, Christopher
Mares, David
Mares, David
Maulik, Ujjwal
Mekaru, Sumiko
Mekaru, Sumiko
Memory, Alex
Memory, Alex
Miao, Hui
Miao, Hui
Michelson, Matthew
Mihalkova, Lilyana
Milic-Frayling, Natasa
Miller, Renee
Miller, Renee J
Minton, Steve
Minton, Steven
Mitkus, Shruti
Moens, Marie-Francine
Motoda, Hiroshi
Mount, Stephen
Moustafa, Walaa Eldin
Moustafa, Walaa
Moustafa, Walaa
Muggleton, Stephen
Mustafa, Bilgic
Muthiah, Sathappan
Myra, Norton
Namata, Galileo Mark
Namata, Galileo
Namata, Galileo
Navlakha, Saket
Nikolov, Nikola S.
Norman, Joseph
Norton, Myra
Nsoesie, Elaine
Nsoesie, Elaine
Ntoulas, Alexcandros
O'Donovan, John
O'Leary, Dianne
ODonovan, John
Oard, Doug
Odonovan, John
Onukwugha, Eberechukwu
Ottosson, Gregor
Panagiotis, Papadimitriou
Panayiotis, Tsaparas
Parikh, Harsh
Pfeffer, Avi
Pfeffer, Avi
Piatetsky-Shapiro, Gregory
Plangprasopchok, Anon
Polymeropoulos, Mihales
Polyzotis, Neoklis
Pujara, Jay
Pujara, Jay
Ramakrishnan, Naren
Ramakrishnan, Naren
Ramesh, Arti
Ramesh, Arti
Rand, William
Rao, Nikhil S
Raschid, Louiqa
Raschid, Louiqa
Rastegari, Mohammad
Rathod, Priyang
Rekatsinas, Theodoros
Rekatsinas, Theodoros
Rhee, Jeanne
Riloff, Ellen
Rodrigues, Eduarda Mendes
Rodriguez, Mario
Roussopoulos, Nick
Roy, Sudeepa
Saha, Barna
Sahami, Mehran
Salami, Babak
Saraf, Parang
Sarawagi, Sunita
Sayyadi, Hassan
Schaffer, James
Schaffer, James
Scheffer, Tobias
Schmidler, Scott
Schnaitter, Karl
See, Kane
Segal, Eran
Sehgal, Vivek
Self, Nathan
Sen, Prithviraj
Sen, Prithviraj
Shahar, Yuval
Sharara, Hossam
Sharara, Hossam
Shashanka, Madhusudana
Shitian, Shen
Shneiderman, Ben
Singh, Lisa
Sisman, Bunyamin
Skomoroch, Peter
Small, Peter
Smith, Marc
Somasundaran, Swapna
Sopan, Awalin
Springer, Aaron
Sridhar, Dhanya
Srinivasan, Aravind
Srinivasan, Sriram
Srivastava, Ashok
Srivastava, Divesh
Srivastava, Divesh
Staats, Brian
Stephen, Bach
Subbaian, Karthik
Subrahmanian, V. S.
Suciu, Dan
Summers, Kristin
Tadepalli, Prasad
Taskar, Benjamin
Terzi, Evimaria
Thompson, Spencer K.
Ting, Hua
Tom, Yeh
Tomkins, Sabina
Tomkins, Sabina
Trinh, Khoa
Udrea, Octavian
Viechnicki, Peter
Volpi, Simona
Vullikanti, Anil
Walker, Marilyn
Wang, Wei
Wei, Hao
Weikum, Gerhard
Weikum, Gerhard
Welser, Howard
Whittaker, Steve
Wiebe, Janyce
Wilbur, John
Wilbur, John
Yu, Philip
Yu, Jun
Zaki, Mohammed
Zavorin, Ilya
Zhang, Yi
Zhang, Yue
Zhao, Liang
Zhao, Bin
Zheleva, Elena
Zheleva, Elena
desJardins, Marie
Type
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Conference Paper
Journal Article
Thesis
Tutorial
Book
Unpublished
Term
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Year
any
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1995
1994
Keyword
any
Cognition
Comparative Analysis
Complexity theory
Data engineering
Discussion Forums
First-order probabilistic models
HL-MRFs
Knowledge engineering
LDA
Lifted inference and learning
MOOC
MOOC Discussion Forums
MOOCs
Metadata
Model Comparison
Online Courses
PAC-Bayes
Par-factor graphs
Probabilistic logic
Probabilistic programming
SRL
Schema mapping
Seeded LDA
Socio-behavioral models
Statistical relational learning
Task analysis
Templated graphical models
Uncertain Graphs
Visualizing Uncertainty
anonymity online
bioinformatics gene expression analysis antipsychotic pharmacogenetics
collective classification
collective mapping discovery
data integration
defect
feature generation
functional biological signals
gene expression bioinformatics drug therapeutics
generalization bounds
groups
high school MOOCs
inference mechanisms
influence
latent variable models
learner engagement
learning analytics
learning theory
meta data
online education
optimisation
optimization
potential mappings
privacy
probabilistic modeling
probabilistic reasoning techniques
probabilistic soft logic
probability
professional networks
schema mapping optimization problem
search
sensitive attribute inference
social media
social networks
splice-site
statistical relational language
structured prediction
student learning
tutorial
uncertainty handling
web
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Title
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B
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E
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K
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P
E. Zheleva
,
“
Prediction, Evolution and Privacy in Social and Affiliation Networks
”
, University of Maryland College Park, 2011.
Google Scholar
BibTex
zheleva-phdthesis11.pdf
(5.81 MB)
L. Licamele
and
Getoor, L.
,
“
Predicting Protein-Protein Interactions Using Relational Features
”
, in
ICML Workshop on Statistical Network Analysis
, 2006.
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BibTex
S. Tomkins
,
Ramesh, A.
, and
Getoor, L.
,
“
Predicting Post-Test Performance from Online Student Behavior: A High School MOOC Case Study
”
, in
EDM
, 2016.
Google Scholar
BibTex
tomkins-edm16.pdf
(619.77 KB)
M. Rastegari
,
Choi, J.
,
Fakhraei, S.
,
III, H. Daume
, and
Davis, L.
,
“
Predictable Dual-View Hashing
”
, in
Proceedings of the 30th International Conference on Machine Learning (ICML-13)
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BibTex
rastegari13.pdf
(2.35 MB)
A. Lansky
and
Getoor, L.
,
“
Practical Planning in COLLAGE
”
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Proceedings of the AAAI Fall Symposium on Planning and Learning: On to Real Applications
, 1994.
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BibTex
P. Sen
,
Deshpande, A.
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Getoor, L.
,
“
PrDB: Managing and Exploiting Rich Correlations in Probabilistic Databases
”
,
VLDB Journal, special issue on uncertain and probabilistic databases
, 2009.
Google Scholar
BibTex
sen-vldbj09.pdf
(1.12 MB)
G. Mark Namata
and
Getoor, L.
,
“
A Pipeline Approach to Graph Identification
”
, in
Seventh International Workshop on Mining and Learning with Graphs
, 2009.
Google Scholar
BibTex
namatag-mlg09.pdf
(93.77 KB)
P. Kouki
,
Schaffer, J.
,
Pujara, J.
,
Odonovan, J.
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Getoor, L.
,
“
Personalized Explanations for Hybrid Recommender Systems
”
, in
Intelligent User Interfaces (IUI)
, 2019.
Google Scholar
BibTex
kouki-iui19.pdf
(3.34 MB)
T. Elsayed
,
Oard, D.
,
Namata, G. Mark
, and
Getoor, L.
,
“
Personal Name Resolution in Email: A Heuristic Approach
”
. University of Maryland, College Park, 2008.
Google Scholar
BibTex
LAMP_150.pdf
(397.61 KB)
S. H. Bach
,
Huang, B.
,
Boyd-Graber, J.
, and
Getoor, L.
,
“
Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs
”
, in
International Conference on Machine Learning (ICML)
, 2015.
Google Scholar
BibTex
bach-icml15.pdf
(356.46 KB)
E. Hung
,
Getoor, L.
, and
Subrahmanian, V. S.
,
“
PXML: A Probabilistic Semistructured Data Model and Algebra
”
, in
Proceedings of the IEEE International Conference on Data Engineering
, 2003.
Google Scholar
BibTex
L. Getoor
and
Grant, J.
,
“
PRL: A Logical Approach to Probabilistic Relational Models
”
,
Machine Learning Journal
, vol. 62, 2006.
Google Scholar
BibTex
getoor-mlj06.pdf
(685.04 KB)
B. London
,
Huang, B.
,
Taskar, B.
, and
Getoor, L.
,
“
PAC-Bayesian Collective Stability
”
, in
Proceedings of the 17th International Conference on Artificial Intelligence and Statistics
, 2014.
Google Scholar
BibTex
london-aistats14.pdf
(490.14 KB)
B. London
,
Huang, B.
,
Taskar, B.
, and
Getoor, L.
,
“
PAC-Bayes Generalization Bounds for Randomized Structured Prediction
”
, in
NIP Workshop on Perturbation, Optimization and Statistics
, 2013.
Google Scholar
BibTex
london-nips13ws.pdf
(205.57 KB)
O
H. Hwang
,
Lauw, H.
,
Getoor, L.
, and
Ntoulas, A.
,
“
Organizing User Search Histories
”
,
IEEE Transactions on Knowledge and Data Engineering
, 2010.
Google Scholar
BibTex
S. Somasundaran
,
Namata, G. Mark
,
Getoor, L.
, and
Wiebe, J.
,
“
Opinion Graphs for Polarity and Discourse Classification
”
, in
TextGraphs-4: Graph-based Methods for Natural Language Processing
, 2009.
Google Scholar
BibTex
somasundaran-textgraphs09.pdf
(289.75 KB)
J. Pujara
,
Miao, H.
,
Getoor, L.
, and
Cohen, W.
,
“
Ontology-Aware Partitioning for Knowledge Graph Identification
”
, in
CIKM Workshop on Automatic Knowledge Base Construction
, 2013.
Google Scholar
BibTex
pujara_akbc13.pdf
(370.62 KB)
L. Getoor
and
Fromherz, M.
,
“
Online Scheduling for Reprographic Machines
”
, in
Working notes AAAI Workshop on Online Search
, 1997.
Google Scholar
BibTex
J. Pujara
,
London, B.
,
Getoor, L.
, and
Cohen, W.
,
“
Online Inference for Knowledge Graph Construction.
”
, in
Workshop on Statistical Relational AI
, 2015.
Google Scholar
BibTex
pujara-starai15.pdf
(340.95 KB)
I. Bhattacharya
and
Getoor, L.
,
“
Online Collective Entity Resolution
”
, in
The 22nd National Conference on Artificial Intelligence (NECTAR Track)
, 2007.
Google Scholar
BibTex
nectar07.pdf
(395.24 KB)
N
S. Fakhraei
,
Huang, B.
,
Raschid, L.
, and
Getoor, L.
,
“
Network-Based Drug-Target Interaction Prediction with Probabilistic Soft Logic
”
,
IEEE/ACM Transactions on Computational Biology and Bioinformatics
, 2014.
Google Scholar
BibTex
fakhraei-tcbb2014_accepted.pdf
(3.97 MB)
C. Diehl
,
Getoor, L.
, and
Namata, G. Mark
,
“
Name Reference Resolution in Organizational Email Archives
”
, in
SIAM Conference on Data Mining (SDM)
, 2006.
Google Scholar
BibTex
diehlsdm06.pdf
(971.2 KB)
M
A. Ramesh
,
Rodriguez, M.
, and
Getoor, L.
,
“
Multi-relational influence models for online professional networks
”
, in
International Conference on Web Intelligence (ICWI)
, 2017, pp. 291-298.
Google Scholar
BibTex
ramesh-icwi17.pdf
(761.17 KB)
B. London
,
Rekatsinas, T.
,
Huang, B.
, and
Getoor, L.
,
“
Multi-relational Weighted Tensor Decomposition
”
, in
NIPS Workshop on SL
, 2012.
Google Scholar
BibTex
london-sl12.pdf
(326.3 KB)
B. London
,
Rekatsinas, T.
,
Huang, B.
, and
Getoor, L.
,
“
Multi-relational Learning Using Weighted Tensor Decomposition with Modular Loss
”
. University of Maryland College Park, 2013.
Google Scholar
BibTex
mrwtd.pdf
(460.45 KB)
L. Getoor
,
“
Multi-relational Data Mining Using Probabilistic Models
”
, in
Multi-Relational Data Mining Workshop
, 2001.
Google Scholar
BibTex
mrdm.pdf
(109.57 KB)
H. Sharara
,
Halgin, D.
,
Getoor, L.
, and
Borgatti, S.
,
“
Multi-dimensional Trajectory Analysis for Career Histories
”
, in
International Sunbelt Social Networks Conference (Sunbelt XXXI)
, 2011.
Google Scholar
BibTex
A. Ramesh
,
Goldwasser, D.
,
Huang, B.
,
III, H. Daume
, and
Getoor, L.
,
“
Modeling Learner Engagement in MOOCs using Probabilistic Soft Logic
”
, in
NIPS Workshop on Data Driven Education
, 2013.
Google Scholar
BibTex
ramesh-nipsws13.pdf
(153.92 KB)
B. Saha
and
Getoor, L.
,
“
On Maximum Coverage in the Streaming Model & Application to Multi-topic Blog-Watch
”
, in
2009 SIAM International Conference on Data Mining (SDM09)
, 2009.
Google Scholar
BibTex
saha-sdm08.pdf
(233.12 KB)
E. Augustine
and
Farnadi, G.
,
“
MLTrain: Collective Reasoning With Probabilistic Soft Logic
”
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Google Scholar
BibTex
augustine-uai18.pdf
(8.93 MB)
L
T. Rekatsinas
,
Deshpande, A.
, and
Getoor, L.
,
“
Local Structure and Determinism in Probabilistic Databases
”
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SIGMOD
, 2012.
Google Scholar
BibTex
rekatsinas-sigmod12.pdf
(490.28 KB)
Q. Lu
and
Getoor, L.
,
“
Link-based Text Classification
”
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IJCAI Workshop on "Text Mining and Link Analysis"
, 2003.
Google Scholar
BibTex
ijcai03-ws.pdf
(97.25 KB)
Q. Lu
and
Getoor, L.
,
“
Link-based Classification Using Labeled and Unlabeled Data
”
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ICML Workshop on "The Continuum from Labeled to Unlabeled Data in Machine Learning and Data Mining
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icml03-ws.pdf
(274.65 KB)
P. Sen
and
Getoor, L.
,
“
Link-based Classification
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senum-tr07.pdf
(511.11 KB)
L. Getoor
,
Link-based Classification
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BibTex
getoor-book05.pdf
(273.43 KB)
Q. Lu
and
Getoor, L.
,
“
Link-based Classification
”
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Proceedings of the International Conference on Machine Learning (ICML)
, 2003.
Google Scholar
BibTex
lu-icml03.pdf
(195.81 KB)
M. Bilgic
and
Getoor, L.
,
“
Link-based Active Learning
”
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NIPS Workshop on Analyzing Networks and Learning with Graphs
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BibTex
mbilgic-nips09wkshp.pdf
(116.35 KB)
G. Mark Namata
and
Getoor, L.
,
“
Link Prediction
”
,
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, 2010.
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BibTex
L. Getoor
and
Diehl, C.
,
“
Link Mining: A Survey
”
,
SigKDD Explorations Special Issue on Link Mining
, vol. 7, 2005.
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L. Getoor
,
“
Link Mining: A New Data Mining Challenge
”
,
SIGKDD Explorations, volume
, vol. 5, p. 85- -89, 2003.
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BibTex
A. Kimmig
,
Mihalkova, L.
, and
Getoor, L.
,
“
Lifted graphical models: a survey
”
,
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, pp. 1-45, 2014.
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BibTex
A. Kimmig
,
Mihalkova, L.
, and
Getoor, L.
,
“
Lifted graphical models: a survey
”
,
Machine Learning Journal
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BibTex
kimmig-mlj15.pdf
(785.58 KB)
S. Srinivasan
,
Babaki, B.
,
Farnadi, G.
, and
Getoor, L.
,
“
Lifted Hinge-Loss Markov Random Fields
”
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BibTex
srinivasan-aaai19.pdf
(417.5 KB)
L. Mihalkova
and
Getoor, L.
,
“
Lifted Graphical Models: A Survey
”
. 2011.
Google Scholar
BibTex
1107.4966v2.pdf
(446.54 KB)
M. Smith
,
Barash, V.
,
Getoor, L.
, and
Lauw, H.
,
“
Leveraging Social Context for Searching Social Media
”
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CIKM Workshop on Search in Social Media
, 2008.
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BibTex
O. Udrea
,
Getoor, L.
, and
Miller, R.
,
“
Leveraging Data and Structure in Ontology Integration
”
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Proceedings of ACM-SIGMOD 2007 International Conference on Management
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BibTex
p449.pdf
(509.48 KB)
L. Mihalkova
,
Moustafa, W. Eldin
, and
Getoor, L.
,
“
Learning to Predict Web Collaborations
”
, in
WSDM Workshop on User Modeling for Web Applications
, 2011.
Google Scholar
BibTex
mihalkova-wikiCollabs.pdf
(353.9 KB)
L. Getoor
,
Friedman, N.
, and
Koller, D.
,
“
Learning Structured Statistical Models from Relational Data
”
,
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, vol. 6, 2002.
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BibTex
L. Getoor
,
“
Learning Statistical Models from Relational Data
”
, Stanford, 2001.
Google Scholar
BibTex
getoor-thesis.pdf
(3.39 MB)
L. Getoor
,
Koller, D.
,
Taskar, B.
, and
Friedman, N.
,
“
Learning Probabilistic Relational Models with Structural Uncertainty
”
, in
Proceedings of the AAAI Workshop on Learning Statistical Models from Relational Data
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Google Scholar
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