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Ackermann, Chris
Aggarwal, Charu
Amantullah, Brian
Arredondo, Jaime
Augustine, Eriq
Augustine*, Eriq
Babaki, Behrouz
Babaki, Behrouz
Bach, Stephen H.
Barash, Vladimir
Beard, Mitchell
Bengio, Yoshua
Bhattacharya, Indrajit
Bilgic, Mustafa
Blake, Brian
Blondeel, Marjon
Borgatti, Steve
Boyd-Graber, Jordan
Bradley, Skaggs
Broecheler, Matthias
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, D.
Daume-III, Hal
Davis, Larry
De Cock, Martine
Deshpande, Amol
Diehl, Christopher
Dietterich, Thomas
Djeraba, Chabane
Domingos, Pedro
Dong, Xin Luna
Doppa, Janardhan
Doyle, Andy
Dzeroski, S.
Eirinaki, Magdalini
Eliassi-Rad, Tina
Elsayed, Tamer
Embar, Varun
Fakhraei, Shobeir
Faloutsos, Christos
Farnadi, Golnoosh
Farnadi, Golnoosh
Fayed, Youssef
Feldman, Ronen
Ford, Jim
Foulds, James
Friedman, Nir
Friedman, Mark
Fromherz, Markus
Fuxman, Ariel
Gallagher, Brian
Gazen, Bora C.
Getoor, Lise
Getoor, Lise
Ghosh, Saurav
Golbeck, Jennifer
Goldwasser, Dan
Grant, John
Grossman, Robert
Grycner, Adam
Guiver, John
Gupta, Dipak
Haidarian-Shahri, Hamid
Halgin, Daniel
He, Xinran
Healy, Patrick
Holder, L.
Hollis, Victoria
Huang, Bert
Hung, Edward
Hwang, Heasoo
III, Hal Daume
Islamaj, Rezarta
Isley, Steve
Jacobs, David
Jr., Nick Short
Kang, Jeonhyung
Kang, Hyunmo
Katz, Graham
Khamis, Sameh
Khandpur, Rupinder
Kim, Jihie
Kim, Sungchul
Kimmig, Angelika
Kimmig, Angelika
Kini, Nikhil
Knoblock, Craig
Koehly, Laura
Koh, Eunyee
Kok, Stanley
Kolcz, Alek
Koller, Daphne
Korkmaz, Gizem
Kouki, Pigi
Kouki, Pigi
Kuhlman, Christopher
Kumar, Shachi
Kuter, Ugur
Lansky, Amy
Lauw, Hady
Lavedan, Christian
Lavrac, N.
Lerman, Kristina
Licamele, Louis
Liu, Xiangyang
Liu, Huan
Liu, Yan
London, Ben
Lu, Qing
Machanavajjhala, Ashwin
Mack, Kendra
Macskassy, Sofus
Mann, Janet
Marathe, Achla
Marcum, Christopher
Mares, David
Maulik, U.
Mekaru, Sumiko
Memory, Alex
Memory, Alex
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
Muggleton, Stephen
Muthiah, Sathappan
Namata, Galileo Mark
Navlakha, Saket
Nikolov, Nikola S.
Norman, Joseph
Norris, Eric
Norton, Myra
Nsoesie, Elaine
Ntoulas, Alexcandros
O'Leary, Dianne P.
ODonovan, John
Oard, Doug
Onukwugha, Eberechukwu
Ottosson, Gregor
Papadimitriou, Panagiotis
Pfeffer, Avi
Piatetsky-Shapiro, Gregory
Plangprasopchok, Anon
Polymeropoulos, Mihales
Polyzotis, Neoklis
Pujara, Jay
Pujara, Jay
Pujra, Jay
Ramakrishnan, Naren
Ramesh, Arti
Ramesh, Arti
Rand, William
Rao, Nikhil S
Raschid, Louiqa
Rastegari, Mohammad
Rathod, Priyang
Reddy, Charu C. Aggarwa
Rekatsinas, Theodoros
Rhee, Jeanne
Riloff, Ellen
Rodrigues, Eduarda Mendes
Rodriguez, Mario
Roussopoulos, Nick
Saha, Barna
Sahami, Mehran
Saraf, Parang
Sarawagi, Sunita
Sayyadi, Hassan
Schaffer, James
Scheffer, Tobias
Schmidler, Scott
Schnaitter, Karl
See, Kane
Segal, Eran
Sehgal, Vivek
Self, Nathan
Sen, Prithviraj
Shahar, Yuval
Sharara, Hossam
Shashanka, Madhusudana
Shen, Shitian
Shneiderman, Ben
Singh, Lisa
Skomoroch, Peter
Small, Peter
Smith, Marc
Somasundaran, Swapna
Sopan, Awalin
Springer, Aaron
Sridhar, Dhanya
Srinivasan, Aravind
Srinivasan, Sriram
Srinivasan*, Sriram
Srivastava, Ashok
Srivastava, Divesh
Staats, Brian
Subbaian, Karthik
Subrahmanian, V. S.
Summers, Kristin
Tadepalli, Prasad
Taskar, Benjamin
Terzi, Evimaria
Thompson, Spencer K.
Ting, Hua
Tomkins, Sabina
Trinh, Khoa
Tsaparas, Panayiotis
Udrea, Octavian
Viechnicki, Peter
Volpi, Simona
Vullikanti, Anil
Walker, Marilyn
Wang, Wei
Weikum, Gerhard
Welser, Howard
Whittaker, Steve
Wiebe, Janyce
Wilbur, John
Yeh, Tom
Yoo, Jaebong
Yu, Jiawei Han Philip
Yu, Jun
Zaki, Mohammed
Zavorin, Ilya
Zhang, Yi
Zhang, Yue
Zhao, Liang
Zhao, Bin
Zheleva, Elena
desJardins, Marie
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Keyword
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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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Author
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Title
Year
A
B
C
D
E
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H
I
J
K
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X
Y
Z
L
Lansky, A.
&
Getoor, L.
Scope and Abstraction: Two Criteria for Localized Planning
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Lansky, A.
,
Friedman, M.
,
Getoor, L.
,
Schmidler, S.
&
Jr., N. Short
.
The Collage/Khoros Link: Planning for Image Processing Tasks
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Lansky, A.
&
Getoor, L.
Practical Planning in COLLAGE
.
Proceedings of the AAAI Fall Symposium on Planning and Learning: On to Real Applications
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Lansky, A.
&
Getoor, L.
Scope and Abstraction: Two Criteria for Localized Planning
.
Proceedings of the Workshop on Theory Reformulation and Abstraction
(1994).
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BibTex
Lerman, K.
,
Getoor, L.
,
Minton, S.
&
Knoblock, C.
Using the Structure of Web Sites for Automatic Segmentation of Tables
.
In Proceedings of ACM-SIGMOD 2004 International Conference on Management of Data
(2004).
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BibTex
lerman-sigmod04.pdf
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Licamele, L.
&
Getoor, L.
A method for the detection of meaningful and reproducible group signatures from gene expression profiles.
Journal of Bioinformatics and Computational Biology
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BibTex
Licamele, L.
&
Getoor, L.
Indirect two-sided relative ranking: a robust similarity measure for gene expression data
.
BMC Bioinformatics
(2010).
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Licamele, L.
&
Getoor, L.
Predicting Protein-Protein Interactions Using Relational Features
.
ICML Workshop on Statistical Network Analysis
(2006).
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Licamele, L.
&
Getoor, L.
Social Capital in Friendship-Event Networks
.
IEEE International Conference on Data Mining (ICDM)
(2006).
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BibTex
Licamele, L.
,
Bilgic, M.
,
Getoor, L.
&
Roussopoulos, N.
Capital and Benefit in Social Networks
.
ACM SIGKDD Workshop on Link Analysis and Group Detection (LinkKDD)
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BibTex
licamele_linkkdd05.pdf
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London, B.
,
Huang, B.
,
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&
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PAC-Bayesian Collective Stability
.
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london-aistats14.pdf
(490.14 KB)
London, B.
et al.
Collective Activity Detection using Hinge-loss Markov Random Fields
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CVPR Workshop on Structured Prediction: Tractability, Learning and Inference
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london-cvpr13.pdf
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London, B.
&
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Data Classification: Algorithms and Applications
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cc-chapter.pdf
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Huang, B.
,
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Collective Stability in Structured Prediction: Generalization from One Example
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london-icml13-long.pdf
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,
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&
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br_risk_bounds.pdf
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London, B.
,
Rekatsinas, T.
,
Huang, B.
&
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Multi-relational Learning Using Weighted Tensor Decomposition with Modular Loss
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mrwtd.pdf
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London, B.
,
Huang, B.
,
Taskar, B.
&
Getoor, L.
PAC-Bayes Generalization Bounds for Randomized Structured Prediction
.
NIP Workshop on Perturbation, Optimization and Statistics
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BibTex
london-nips13ws.pdf
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London, B.
,
Huang, B.
&
Getoor, L.
Improved Generalization Bounds for Large-scale Structured Prediction
.
NIPS Workshop on Algorithmic and Statistical Approaches for Large Social Networks
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BibTex
london-nips12ws.pdf
(213.95 KB)
London, B.
,
Rekatsinas, T.
,
Huang, B.
&
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Multi-relational Weighted Tensor Decomposition
.
NIPS Workshop on Spectral Learning
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london-nips12ws-mrwtd.pdf
(326.3 KB)
London, B.
On the Stability of Structured Prediction
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blondon-thesis.pdf
(1.16 MB)
London, B.
,
Huang, B.
&
Getoor, L.
Stability and Generalization in Structured Prediction
.
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BibTex
london-stability15.pdf
(532.16 KB)
London, B.
,
Huang, B.
&
Getoor, L.
The Benefits of Learning with Strongly Convex Approximate Inference
.
International Conference on Machine Learning (ICML)
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BibTex
london-icml15.pdf
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London, B.
,
Huang, B.
&
Getoor, L.
Stability and Generalization in Structured Prediction
.
Journal of Machine Learning Research
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BibTex
london-jlmr17.pdf
(532.8 KB)
London, B.
,
Huang, B.
&
Getoor, L.
On the Strong Convexity of Variational Inference
.
NIPS Workshop on Advances in Variational Inference
(2014).
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BibTex
london-nips14ws.pdf
(253.72 KB)
Lu, Q.
&
Getoor, L.
Link-based Classification
.
Proceedings of the International Conference on Machine Learning (ICML)
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BibTex
lu-icml03.pdf
(195.81 KB)
Lu, Q.
&
Getoor, L.
Link-based Classification Using Labeled and Unlabeled Data
.
ICML Workshop on "The Continuum from Labeled to Unlabeled Data in Machine Learning and Data Mining
(2003).
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BibTex
icml03-ws.pdf
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Lu, Q.
&
Getoor, L.
Link-based Text Classification
.
IJCAI Workshop on "Text Mining and Link Analysis"
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BibTex
ijcai03-ws.pdf
(97.25 KB)
M
Memory, A.
,
Kimmig, A.
,
Bach, S. H.
,
Raschid, L.
&
Getoor, L.
Graph Summarization in Annotated Data Using Probabilistic Soft Logic
.
Proceedings of the International Workshop on Uncertainty Reasoning for the Semantic Web (URSW)
(2012).
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BibTex
mrc_iswc12_ws.pdf
(411.71 KB)
Miao, H.
,
Liu, X.
,
Huang, B.
&
Getoor, L.
A Hypergraph-Partitioned Vertex Programming Approach for Large-scale Consensus Optimization
.
2013 IEEE International Conference on Big Data
(2013).
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BibTex
miao-bd13.pdf
(307.51 KB)
Mihalkova, L.
,
Moustafa, W. Eldin
&
Getoor, L.
Learning to Predict Web Collaborations
.
WSDM Workshop on User Modeling for Web Applications
(2011).
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BibTex
mihalkova-wikiCollabs.pdf
(353.9 KB)
Mihalkova, L.
&
Getoor, L.
Lifted Graphical Models: A Survey
. (2011).
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BibTex
1107.4966v2.pdf
(446.54 KB)
Minton, S.
et al.
Improving Classifier Performance by Autonomously Collecting Background Knowledge from the Web
.
Tenth International Conference on Machine Learning and Applications
(2011).
Google Scholar
BibTex
minton-icmla2011.pdf
(733.09 KB)
Moustafa, W. Eldin
,
Kimmig, A.
,
Deshpande, A.
&
Getoor, L.
Subgraph Pattern Matching over Uncertain Graphs with Identity Linkage Uncertainty
.
International Conference on Data Engineering (ICDE)
(2014).
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BibTex
ICDE14_conf_full_374.pdf
(1.57 MB)
Moustafa, W. Eldin
,
Miao, H.
,
Deshpande, A.
&
Getoor, L.
GrDB: A System for Declarative and Interactive Analysis of Noisy Information Networks
.
ACM SIGMOD Conference
(2013).
Google Scholar
BibTex
sigmod13.pdf
(1.1 MB)
Moustafa, W. Eldin
,
Deshpande, A.
&
Getoor, L.
Ego-centric Graph Pattern Census
.
International Conference on Data Engineering (ICDE)
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BibTex
moustafaicde.pdf
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Moustafa, W. Eldin
,
Namata, G. Mark
,
Deshpande, A.
&
Getoor, L.
Declarative Analysis of Noisy Information Networks
.
ICDE Workshop on Graph Data Management: Techniques and Applications
(2011).
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BibTex
moustafa-gdm11.pdf
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Muthiah, S.
et al.
Capturing Planned Protests from Open Source Indicators
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muthiah-aimag16.pdf
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N
Namata, G. Mark
.
Identifying Graphs from Noisy Observational Data
. (2012).
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namata-phdthesis.pdf
(1.51 MB)
Namata, G. Mark
,
London, B.
,
Getoor, L.
&
Huang, B.
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.
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BibTex
namata-mlg12.pdf
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Namata, G. Mark
,
Kok, S.
&
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.
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BibTex
namata-kdd11.pdf
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Namata, G. Mark
,
Sharara, H.
&
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(
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Namata, G. Mark
&
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Encyclopedia of Machine Learning
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Namata, G. Mark
&
Getoor, L.
A Pipeline Approach to Graph Identification
.
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BibTex
namatag-mlg09.pdf
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Namata, G. Mark
,
Sen, P.
,
Bilgic, M.
&
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Text Mining: Classification, Clustering, and Applications
(
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&
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Namata, G. Mark
&
Getoor, L.
Identifying Graphs From Noisy and Incomplete Data
.
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BibTex
namatag-kddu09.pdf
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Namata, G. Mark
,
Staats, B.
,
Getoor, L.
&
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.
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cikm0671-namata.pdf
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Namata, G. Mark
,
Getoor, L.
&
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.
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BibTex
icml2006_ExtAbst.pdf
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Namata, G. Mark
,
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&
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.
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BibTex
namata-tkdd.pdf
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P
Papadimitriou, P.
,
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,
Fuxman, A.
&
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.
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Piatetsky-Shapiro, G.
et al.
Is there a grand challenge or X-prize for data mining?
.
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BibTex
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