Skip to main content
LINQS
Statistical Relational Learning Group
Navigation
Main
menu
Home
People
Publications
Authors
Keywords
Data
History
Contact
Publications
Search
Show only items where
Author
any
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
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
Type
any
Conference Paper
Journal Article
Thesis
Tutorial
Book Chapter
Unpublished
Poster
Book
Term
any
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
Export 39 results:
BibTex
Author
[
Title
]
Year
Filters:
Author
is
Huang, Bert
[Clear All Filters]
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
P
Q
R
S
T
U
V
W
X
Y
Z
B
Ramakrishnan, N.
et al.
‘Beating the news’ with EMBERS: Forecasting Civil Unrest using Open Source Indicators
.
ACM SIGKDD Conference on Knowledge Discovery and Data Mining
(2014).
Google Scholar
BibTex
ramakrishnan-kdd14.pdf
(1.15 MB)
London, B.
,
Huang, B.
&
Getoor, L.
The Benefits of Learning with Strongly Convex Approximate Inference
.
International Conference on Machine Learning (ICML)
(2015).
Google Scholar
BibTex
london-icml15.pdf
(788.06 KB)
C
Muthiah, S.
et al.
Capturing Planned Protests from Open Source Indicators
.
AI Magazine
37,
63–75 (2016).
Google Scholar
BibTex
muthiah-aimag16.pdf
(1.23 MB)
London, B.
et al.
Collective Activity Detection using Hinge-loss Markov Random Fields
.
CVPR Workshop on Structured Prediction: Tractability, Learning and Inference
(2013).
Google Scholar
BibTex
london-cvpr13.pdf
(705.87 KB)
Fakhraei, S.
,
Huang, B.
&
Getoor, L.
Collective Inference and Multi-Relational Learning for Drug–Target Interaction Prediction
.
NIPS Workshop on Machine Learning in Computational Biology (MLCB)
(2013).
Google Scholar
BibTex
London, B.
,
Huang, B.
,
Taskar, B.
&
Getoor, L.
Collective Stability in Structured Prediction: Generalization from One Example
.
Proceedings of the 30th International Conference on Machine Learning (ICML-13)
(2013).
Google Scholar
BibTex
london-icml13-long.pdf
(373.82 KB)
Sridhar, D.
,
Foulds, J.
,
Huang, B.
,
Walker, M.
&
Getoor, L.
Collective classification of stance and disagreement in online debate forums
.
Bay Area Machine Learning Symposium (BayLearn)
(2014).
Google Scholar
BibTex
E
Huang, B.
,
London, B.
,
Taskar, B.
&
Getoor, L.
Empirical Analysis of Collective Stability
.
ICML Workshop on Structured Learning (SLG)
(2013).
Google Scholar
BibTex
huang-slg13.pdf
(237.81 KB)
F
Huang, B.
,
Kimmig, A.
,
Getoor, L.
&
Golbeck, J.
A Flexible Framework for Probabilistic Models of Social Trust
.
The 2013 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction (SBP 2013)
(2013).
Google Scholar
BibTex
huang-sbp13.pdf
(247.2 KB)
G
London, B.
,
Huang, B.
&
Getoor, L.
Graph-based Generalization Bounds for Learning Binary Relations
. (2013).
Google Scholar
BibTex
br_risk_bounds.pdf
(304.54 KB)
H
Bach, S. H.
,
Broecheler, M.
,
Huang, B.
&
Getoor, L.
Hinge-Loss Markov Random Fields and Probabilistic Soft Logic
.
Journal of Machine Learning Research (JMLR)
18,
1-67 (2017).
Google Scholar
BibTex
bach-jmlr17.pdf
(731.56 KB)
Bach, S. H.
,
Broecheler, M.
,
Huang, B.
&
Getoor, L.
Hinge-Loss Markov Random Fields and Probabilistic Soft Logic
.
ArXiv:1505.04406 [cs.LG]
(2015).
Google Scholar
BibTex
bach-arxiv15.pdf
(686.27 KB)
Bach, S. H.
,
Huang, B.
,
London, B.
&
Getoor, L.
Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction
.
Uncertainty in Artificial Intelligence
(2013).
Google Scholar
BibTex
bach-uai13.pdf
(379.45 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).
Google Scholar
BibTex
miao-bd13.pdf
(307.51 KB)
I
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
(2012).
Google Scholar
BibTex
london-nips12ws.pdf
(213.95 KB)
Ramesh, A.
,
Goldwasser, D.
,
Huang, B.
,
Daume-III, H.
&
Getoor, L.
Interpretable Engagement Models for MOOCs using Hinge-loss Markov Random Fields
.
Transactions on Learning Technologies
(2019).
Google Scholar
BibTex
ramesh-tlt19.pdf
(4.3 MB)
J
Sridhar, D.
,
Foulds, J.
,
Walker, M.
,
Huang, B.
&
Getoor, L.
Joint Models of Disagreement and Stance in Online Debate
.
Annual Meeting of the Association for Computational Linguistics (ACL)
(2015).
Google Scholar
BibTex
sridhar-acl15.pdf
(227.14 KB)
L
Bach, S. H.
,
Huang, B.
&
Getoor, L.
Large-margin Structured Learning for Link Ranking
.
NIPS Workshop on Frontiers of Network Analysis: Methods, Models, and Applications
(2013).
Google Scholar
BibTex
bach-fna13.pdf
(210.09 KB)
Ramesh, A.
,
Goldwasser, D.
,
Huang, B.
,
III, H. Daume
&
Getoor, L.
Learning Latent Engagement Patterns of Students in Online Courses
.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence
(AAAI Press, 2014).
Google Scholar
BibTex
ramesh-aaai14.pdf
(505.47 KB)
Bach, S. H.
,
Huang, B.
&
Getoor, L.
Learning Latent Groups with Hinge-loss Markov Random Fields
.
ICML Workshop on Inferning: Interactions between Inference and Learning
(2013).
Google Scholar
BibTex
bach-inferning13.pdf
(348.79 KB)
M
Ramesh, A.
,
Goldwasser, D.
,
Huang, B.
,
III, H. Daume
&
Getoor, L.
Modeling Learner Engagement in MOOCs using Probabilistic Soft Logic
.
NIPS Workshop on Data Driven Education
(2013).
Google Scholar
BibTex
ramesh-nipsws13.pdf
(153.92 KB)
London, B.
,
Rekatsinas, T.
,
Huang, B.
&
Getoor, L.
Multi-relational Learning Using Weighted Tensor Decomposition with Modular Loss
. (2013).
Google Scholar
BibTex
mrwtd.pdf
(460.45 KB)
London, B.
,
Rekatsinas, T.
,
Huang, B.
&
Getoor, L.
Multi-relational Weighted Tensor Decomposition
.
NIPS Workshop on Spectral Learning
(2012).
Google Scholar
BibTex
london-nips12ws-mrwtd.pdf
(326.3 KB)
N
Fakhraei, S.
,
Huang, B.
,
Raschid, L.
&
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)
P
London, B.
,
Huang, B.
,
Taskar, B.
&
Getoor, L.
PAC-Bayes Generalization Bounds for Randomized Structured Prediction
.
NIP Workshop on Perturbation, Optimization and Statistics
(2013).
Google Scholar
BibTex
london-nips13ws.pdf
(205.57 KB)
London, B.
,
Huang, B.
,
Taskar, B.
&
Getoor, L.
PAC-Bayesian Collective Stability
.
Proceedings of the 17th International Conference on Artificial Intelligence and Statistics
(2014).
Google Scholar
BibTex
london-aistats14.pdf
(490.14 KB)
Bach, S. H.
,
Huang, B.
,
Boyd-Graber, J.
&
Getoor, L.
Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs
.
International Conference on Machine Learning (ICML)
(2015).
Google Scholar
BibTex
bach-icml15.pdf
(356.46 KB)
Bach, S. H.
,
Huang, B.
&
Getoor, L.
Probabilistic Soft Logic for Social Good
.
KDD Workshop on Data Science for Social Good
(2014).
Google Scholar
BibTex
bach-dssg14.pdf
(124.88 KB)
Huang, B.
,
Kimmig, A.
,
Getoor, L.
&
Golbeck, J.
Probabilistic Soft Logic for Trust Analysis in Social Networks
.
International Workshop on Statistical Relational Artificial Intelligence (StaRAI 2012)
(2012).
Google Scholar
BibTex
huang-starai12.pdf
(241.96 KB)
Q
Namata, G. Mark
,
London, B.
,
Getoor, L.
&
Huang, B.
Query-driven Active Surveying for Collective Classification
.
Workshop on Mining and Learning with Graphs
(2012).
Google Scholar
BibTex
namata-mlg12.pdf
(257.49 KB)
R
Bach, S. H.
,
Huang, B.
&
Getoor, L.
Rounding Guarantees for Message-Passing MAP Inference with Logical Dependencies
.
NIPS Workshop on Discrete and Combinatorial Problems in Machine Learning (DISCML)
(2014).
Google Scholar
BibTex
bach-discml14.pdf
(254.9 KB)
S
Kimmig, A.
,
Bach, S. H.
,
Broecheler, M.
,
Huang, B.
&
Getoor, L.
A Short Introduction to Probabilistic Soft Logic
.
NIPS Workshop on Probabilistic Programming: Foundations and Applications
(2012).
Google Scholar
BibTex
psl_pp12.pdf
(164.6 KB)
Huang, B.
,
Bach, S. H.
,
Norris, E.
,
Pujara, J.
&
Getoor, L.
Social Group Modeling with Probabilistic Soft Logic
.
NIPS 2012 Workshop - Social Network and Social Media Analysis: Methods, Models, and Applications
(2012).
Google Scholar
BibTex
London, B.
,
Huang, B.
&
Getoor, L.
Stability and Generalization in Structured Prediction
.
–
(2015).
Google Scholar
BibTex
london-stability15.pdf
(532.16 KB)
London, B.
,
Huang, B.
&
Getoor, L.
Stability and Generalization in Structured Prediction
.
Journal of Machine Learning Research
17,
(2016).
Google Scholar
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).
Google Scholar
BibTex
london-nips14ws.pdf
(253.72 KB)
U
Ramesh, A.
,
Goldwasser, D.
,
Huang, B.
,
III, H. Daume
&
Getoor, L.
Uncovering Hidden Engagement Patterns for Predicting Learner Performance in MOOCs
.
ACM Conference on Learning at Scale
(ACM, 2014).
Google Scholar
BibTex
Ramesh, A.
,
Goldwasser, D.
,
Huang, B.
,
III, H. Daume
&
Getoor, L.
Understanding MOOC Discussion Forums using Seeded LDA
.
9th ACL Workshop on Innovative Use of NLP for Building Educational Applications
(ACL, 2014).
Google Scholar
BibTex
ramesh-aclws14.pdf
(137.57 KB)
Bach, S. H.
,
Huang, B.
&
Getoor, L.
Unifying Local Consistency and MAX SAT Relaxations for Scalable Inference with Rounding Guarantees
.
Artificial Intelligence and Statistics (AISTATS)
(2015).
Google Scholar
BibTex
bach-aistats15.pdf
(345.2 KB)