
Selected Papers
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2016
K. Tang, N. Ruozzi, D. Belanger, and T. Jebara. "Bethe learning of graphical models via MAP decoding" . International Conference on Artificial Intelligence and Statistics (AISTATS), 2016.
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2015
B. Kapicioglu, D. Rosenberg, R. Schapire and T. Jebara, "Collaborative place models" . International Joint Conferences on Artificial Intelligence (IJCAI), 2015.
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K. Choromanski and T. Jebara. "Coloring tournaments with forbidden substructures" .
Technical report on the arXiv, April, 2015.
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K. Tang, N. Ruozzi, D. Belanger and T. Jebara. "Bethe learning of conditional random fields via MAP decoding" .
Technical report on the arXiv, March, 2015.
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K.Tang, H. Gubert, R. Tonge, A. Wang, L. Wu, D. Campbell, C. Kedzie, L. Wang, A. Russell, A. Kimball, A. Kambadur, G. Mann, S. Pacifico, J. Hodson, D. Yao,K. McKeown, T. Jebara, "Learning a graphical model of Bloomberg financial and news data" . Data, Algorithms and Problems on Graphs (DAPG) Workshop, 2015.
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E. Taralova, T. Jebara, R.Yuste, "Functional models of mouse visual cortex" . Data, Algorithms and Problems on Graphs (DAPG) Workshop, 2015.
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2014
A. Weller and T. Jebara, "Clamping variables and approximate inference" . Neural Information Processing Systems (NIPS), 2014.
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N. Ruozzi and T. Jebara, "Making pairwise binary graphical models attractive" . Neural Information Processing Systems (NIPS), 2014.
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A. Weller and T. Jebara, "Approximating
the Bethe partition function" . Uncertainty in Artificial Intelligence (UAI), 2014.
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A. Weller, K. Tang, D. Sontag and T. Jebara, "Understanding the Bethe approximation: When and how
can it go wrong?" . Uncertainty in Artificial Intelligence (UAI), 2014.
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S.M. Bellovin, R.M. Hutchins, T. Jebara and
S. Zimmeck, "When enough is enough: Location tracking, mosaic theory
and machine learning" . 8 New York University Journal of Law & Liberty
556, 2014.
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A. Aravkin, A. Choromanska, T. Jebara, and D. Kanevsky. "Semistochastic quadratic bound methods" . Second International Conference
on Learning Representations, (ICLR), Workshop Proceedings, 2014.
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B. Kapicioglu, D. Rosenberg, R. Schapire, and
T. Jebara. "Collaborative ranking for local preferences" .
Seventeenth International Conference on Artificial Intelligence and
Statistics (AISTATS), April 2014.
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F. Xu, K. Choromanski, S. Kumar, T. Jebara and S.F. Chang. "On learning from label proportions" .
Technical report on the arXiv, February, 2014.
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T. Jebara.
"Perfect graphs and graphical modeling" .
In
Tractability: Practical Approaches to Hard Problems,
Edited by Lucas Bordeaux, Youssef Hamadi, Pushmeet Kohli, and Robert Mateescu, Cambridge University Press, 2014.
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2013
K. Choromanski, T. Jebara and K. Tang.
"Adaptive anonymity via bmatching" .
Neural Information Processing Systems (NIPS), December 2013.
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J. Merel, R. Fox, T. Jebara, and L. Paninski.
"A multiagent control framework for coadaptation in braincomputer interfaces" .
Neural Information Processing Systems (NIPS), December 2013.
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K. Tang, A. Weller and T. Jebara.
"Network ranking with Bethe pseudomarginals" .
Neural Information Processing Systems (NIPS), Workshop on Discrete Optimization in Machine Learning, December 2013.
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A. Choromanska, H. Kim, T. Jebara,
M. Mohan and C. Monteleoni.
"Fast spectral
clustering via the Nystrom method" .
Algorithmic Learning Theory (ALT), October 2013.
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A. Weller and T. Jebara.
"On MAP inference by MWSS on perfect graphs" .
Uncertainty in Artificial Intelligence (UAI), July 2013.
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F.X. Yu, D. Liu, S. Kumar, T. Jebara, and S.F. Chang. " ∝ SVM for learning with label proportions" .
International Conference on Machine Learning (ICML), June 2013.
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S. Bellovin, R. Hutchins, T. Jebara and
S. Zimmeck. "When enough is enough: Location tracking, mosaic theory
and machine learning" .
Privacy Law Scholars Conference (PLSC), June 2013.
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J. Wang, T. Jebara and S.F. Chang.
"Semisupervised learning using greedy maxcut" .
Journal of Machine Learning Research (JMLR), 14(Mar):771800, 2013.
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A. Weller and T. Jebara.
"Bethe bounds and approximating the global optimum" .
Sixteenth International Conference on Artificial Intelligence and Statistics (AISTATs), April 2013.
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2012
T. Jebara and A. Choromanska.
"Majorization for CRFs and latent likelihoods" .
Neural Information Processing Systems (NIPS), December 2012.
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A. Weller and T. Jebara.
"Bethe bounds and approximating the global optimum" .
arXiv:1301.0015 and CUCS Tech Report 02212 and 2013 Information Theory and Applications Workshop (ITA), December 2012.
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2011
B. Shaw, B. Huang and T. Jebara.
"Learning a distance metric from a network" .
Neural Information Processing Systems (NIPS), December 2011.
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P. Shivaswamy and T. Jebara.
"Variance penalizing AdaBoost" .
Neural Information Processing Systems (NIPS), December 2011.
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B. Huang, B. Shaw and T. Jebara.
"Learning a degreeaugmented distance metric from a network" .
Beyond
Mahalanobis: Supervised LargeScale Learning of Similarity Workshop,
Neural Information Processing Systems (NIPS), December 2011.
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Y. Song, S. Stolfo and T. Jebara.
"Behaviorbased network traffic synthesis" .
IEEE International
Conference on Technologies for Homeland Security (IEEE HST), November 2011.
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Y. Song, S. Stolfo and T. Jebara.
"Markov models for networkbehavior modeling and anonymization" .
Columbia University, Computer Science Technical Report, CUCS02911, 2011.
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B. Kapicioglu, D. Rosenberg, R. Schapire, and
T. Jebara.
"Place recommendation with implicit spatial
feedback" .
New York Academy of Sciences, Machine Learning Symposium,
October 2011.
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A. Moghadam, T. Jebara and H. Schulzrinne.
"A Markov routing algorithm for mobile DTNs based on
spatiotemporal modeling of human movement data" .
Fourteenth ACM
International Conference on Modeling, Analysis and Simulation of
Wireless and Mobile Systems (MSWiM), 2011.
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B. Huang and T. Jebara.
"Fast bmatching via sufficient selection belief propagation" .
Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATs), April 2011.
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T. Jebara.
"Multitask sparsity via maximum entropy discrimination" .
Journal of Machine Learning Research (JMLR), 12(Jan):75110, 2011.
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2010
P. Shivaswamy and T. Jebara.
"Laplacian spectrum learning" .
European Conference on Machine Learning (ECML), 2010.
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P. Shivaswamy and T. Jebara.
"Empirical Bernstein boosting" .
Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATs), May 2010.
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B. Huang and T. Jebara.
"Collaborative filtering via rating concentration" .
Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATs), May 2010.
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T. Jebara.
"Graphical modeling and inference with perfect graphs" .
The Learning Workshop, April 2010.
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P. Shivaswamy and T. Jebara.
"Maximum relative margin and datadependent regularization" .
Journal of Machine Learning Research (JMLR), 11(Feb):747788,
2010.
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2009
T. Jebara.
"MAP estimation, message passing, and perfect graphs" .
Uncertainty in Artificial Intelligence (UAI), June 2009. Update: the runtime of GroLovSch's method was corrected.
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B. Shaw and T. Jebara.
"Structure preserving embedding" .
International Conference on Machine Learning (ICML), June 2009.
BEST PAPER AWARD
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T. Jebara, J. Wang and S.F. Chang.
"Graph construction and bmatching for semisupervised
learning" .
International Conference on Machine Learning (ICML), June 2009.
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B. Huang and T. Jebara.
"Exact graph structure estimation with degree priors" .
International Conference on Machine Learning and Applications (ICMLA), December 2009.
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P. Shivaswamy and T. Jebara.
"Structured prediction with relative margin" .
International Conference on Machine Learning and Applications (ICMLA), December 2009.
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A. Howard and T. Jebara.
"Transformation learning via kernel alignment" .
International Conference on Machine Learning and Applications (ICMLA), December 2009.
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A. Weller, D. Ellis and T. Jebara.
"Structured prediction models for chord transcription of music audio" .
International Conference on Machine Learning and Applications (ICMLA), December 2009.
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D. Lazer, A. Pentland, L. Adamic, S. Aral, A.L. Barabasi, D. Brewer, N. Christakis, N. Contractor, J. Fowler, M. Gutmann, T. Jebara, G. King, M. Macy, D. Roy, and M. Van Alstyne.
"Computational social science" .
Science, February 6 2009.
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C. Lima, U. Lall, T. Jebara, and
A.G. Barnston. "Statistical prediction of ENSO from subsurface sea
temperature using a nonlinear dimensionality reduction" .
Journal of Climate, Volume 22, Number 17, Pages 45014519, September 1, 2009.
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B. Huang and T. Jebara. "Approximating the permanent with belief propagation" .
Technical report on the arXiv, August 12, 2009.
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B. Shaw and T. Jebara. "Dimensionality reduction, clustering, and PlaceRank applied to spatiotemporal flow data" .
New York Academy of Sciences  Machine Learning Symposium, November, 2009.
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M. Loecher and T. Jebara. "CitySense: Multiscale space time clustering of GPS points and trajectories" .
Proceedings of the Joint Statistical Meeting (JSM), August, 2009.
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2008
P. Shivaswamy and T. Jebara.
"Relative margin machines" .
Neural Information Processing Systems 21 (NIPS), December 2008.
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B. Huang and T. Jebara.
"Maximum likelihood graph structure estimation with degree distributions" .
Analyzing Graphs: Theory and Applications, NIPS Workshop. December 2008.
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B. Shaw and T. Jebara.
"Visualizing graphs with structure preserving embedding" .
Analyzing Graphs: Theory and Applications, NIPS Workshop. December 2008
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W. Jiang, S.F. Chang, T. Jebara and A.C. Loui.
"Semantic concept classification by joint semisupervised learning of feature subspaces and support vector machines" .
European Conference on Computer Vision (ECCV). October 2008.
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T. Jebara.
"Bayesian outtrees" .
Uncertainty in Artificial Intelligence (UAI), July 2008.
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T. Jebara.
"Outtree dependent nonparametric Bayesian inference"
.
Workshop on Nonparameteric Bayes, July 2008.
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J. Wang, T. Jebara and S.F. Chang.
"Graph transduction via alternating minimization" .
International Conference on Machine Learning (ICML), July 2008.
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T. Jebara.
"Learning from outtree dependent data" .
The Learning Workshop, April 2008.
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2007
T. Jebara, Y. Song and K. Thadani.
"Density estimation under independent similarly distributed sampling assumptions" .
Neural Information Processing Systems 20 (NIPS), December 2007.
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A. Howard and T. Jebara.
"Learning monotonic transformations for classification" .
Neural Information Processing Systems 20 (NIPS), December 2007.
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S. Andrews and T. Jebara.
"Graph reconstruction with degreeconstrained subgraphs" .
Workshop on Statistical Network Models (NIPS), December 2007.
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B. Huang and T. Jebara. "Approximating the permanent with belief propagation" .
New York Academy of Sciences  Machine Learning Symposium, 2007.
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B. Shaw and T. Jebara.
"Minimum volume embedding" .
Artificial Intelligence and Statistics (AISTATs), March 2007.
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B. Huang and T. Jebara. "Loopy belief
propagation for bipartite maximum weight bmatching" .
Artificial Intelligence and Statistics (AISTATs), March 2007.
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P. Shivaswamy and T. Jebara. "Ellipsoidal kernel machines" .
Artificial Intelligence and Statistics (AISTATs), March 2007.
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R. Kondor, A. Howard and T. Jebara.
"Multiobject tracking with representations of the symmetric group" .
Artificial Intelligence and Statistics (AISTATs), March 2007.
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T. Jebara, Y. Song and K. Thadani.
"Spectral clustering and embedding with hidden Markov models" .
European Conference on Machine Learning (ECML), September 2007.
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T. Jebara, B. Shaw and A. Howard. "Optimizing eigengaps and spectral functions using iterated SDP" .
The Learning Workshop, 2007.
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2006
R. Kondor and T. Jebara. "Gaussian and Wishart hyperkernels" .
Neural
Information Processing Systems 19 (NIPS), December 2006.
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M. Mandel, D. Ellis and T. Jebara. "An EM algorithm for localizing multiple sound sources in reverberant
environments" .
In Neural
Information Processing Systems 19 (NIPS), December 2006.
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S. Andrews and T. Jebara.
"Structured network learning" .
Workshop on Learning to Compare Examples (NIPS), December 2006.
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T. Jebara and V. Shchogolev.
"Bmatching for spectral clustering" .
European Conference on Machine Learning (ECML), September 2006.
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D. Lewis, T. Jebara and W.S. Noble.
"Support vector machine learning from heterogeneous data: An empirical analysis using protein sequence and structure" .
Bioinformatics. 22(22):27532760, 2006.
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P. Shivaswamy and T. Jebara.
"Permutation invariant SVMs" .
International Conference on Machine Learning (ICML), June 2006.
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D. Lewis, T. Jebara and W. Noble.
"Nonstationary kernel combination" .
International Conference on Machine Learning (ICML), June 2006.
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T. Jebara, B. Shaw and V. Shchogolev.
"Bmatching for embedding" .
The Learning Workshop, April 2006.
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2005
I. R. Kondor, G. Csanyi, S.E. Ahnert and T. Jebara.
"Multi facet learning in Hilbert spaces" .
Columbia University, Computer Science Technical Report, CUCS05405. 2005.
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T. Jebara and P. Long.
"Tree dependent identically distributed learning" .
Columbia University, Computer Science Technical Report, CUCS05005. 2005.
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A. Howard and T. Jebara.
"Square root propagation" .
Columbia University, Computer Science Technical Report, CUCS04005. 2005.
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K. Nishino, S.K. Nayar and T. Jebara.
"Clustered blockwise PCA for representing visual data" .
IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 27, No. 10, p. 1675, October 2005. PDF  BIB
2004
T. Jebara, R. Kondor and A. Howard.
"Probability product kernels" . Journal of Machine Learning
Research (JMLR), Special Topic on Learning Theory, 5(Jul):819844,
2004. PDF  BIB  CODE
A. Howard and T. Jebara. "Dynamical systems trees"
.
Uncertainty in Artificial Intelligence (UAI), July 2004.
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T. Jebara. "Kernelizing sorting, permutation and alignment for minimum volume PCA"
.
Conference on Learning Theory (COLT), July 2004.
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T. Jebara. "Multitask feature and kernel selection for SVMs"
.
International Conference on Machine Learning (ICML), July 2004.
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R. Pelossof, A. Miller, P. Allen and T. Jebara. "An SVM learning approach to robotic grasping" . Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), May 2004.
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T. Jebara, and Y. Bengio. "Orbit learning using convex optimization" . The Learning Workshop, April 2004.
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R. Kondor, T. Jebara, G. Csanyi, S. Ahnert. "Learning from derivatives and other linear functionals" . The Learning Workshop, April 2004.
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J. Triesch and T. Jebara, Editors.
Proceedings of the 2004 International Conference on Development and Learning (ICDL), October 2004. PDF  BIB
2003
T. Jebara. Machine learning: Discriminative and generative .
Kluwer, 2003. ISBN 1402076479.
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T. Jebara. "Images as bags of pixels" .
International Conference on Computer Vision (ICCV), 2003.
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T. Jebara and R. Kondor. "Bhattacharyya and expected likelihood kernels" .
Conference on Learning Theory (COLT), 2003.
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R. Kondor and T. Jebara. "A kernel between sets of vectors" .
International Conference on Machine Learning (ICML), 2003.
BEST STUDENT PAPER AWARD
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T. Jebara. "Convex invariance learning" .
Artificial Intelligence and Statistics (AISTATs), 2003.
(Longer Version)
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2002
T. Jebara and A. Pentland. "Statistical imitative learning from perceptual data" .
2nd International Conference on Development and Learning (ICDL), June 2002.
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A. Kundaje, O. Antar, T. Jebara and C. Leslie.
"Learning regulatory networks from sparsely sampled time series
Expression Data" . Technical Report, 2002. PDF  BIB
2001
T. Jebara. Discriminative, generative and imitative learning .
PhD Thesis, Media Laboratory, MIT, December 2001.
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B. Schiele, T. Jebara, and N. Oliver. "Sensory
augmented computing: Wearing the museum's guide" .
IEEE Micro 21 (3),
May 2001.
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2000
T. Jebara, and A. Pentland. "On reversing Jensen's inequality" .
In Neural
Information Processing Systems 13 (NIPS), December 2000.
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B. Moghaddam, T. Jebara, and A. Pentland. "Bayesian face recognition" .
Pattern Recognition, Vol 33:11, pps 17711782. November 2000.
HONORABLE MENTION AWARD
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T. Jebara, Y. Ivanov, A. Rahimi and A. Pentland. "Tracking conversational context for machine mediation of human discourse" .
In AAAI Fall 2000 Symposium  Socially Intelligent Agents  The Human in the Loop. Nov. 2000.
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T. Jebara and T. Jaakkola. "Feature selection and dualities in maximum entropy
discrimination" .
In 16th Conference on Uncertainty in Artificial Intelligence (UAI), July 2000. Note the typo: E_P{\theta_i,s_i} = Logistic[ 0.5 W_i^2 + \log \frac{p_0}{1p_0} ] W_i.
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1999
T. Jaakkola, M. Meila and T. Jebara. "Maximum entropy discrimination" . In Neural
Information Processing Systems 12 (NIPS), December 1999.
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J. Strom, T. Jebara, S. Basu, and A. Pentland. "Real time tracking and modeling of faces: An EKFbased analysis by
synthesis approach" .
Proceedings of the Modelling People Workshop at
ICCV, August 1999.
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T. Jebara, A. Azarbayejani, and A. Pentland. "3D structure from 2D motion" . In IEEE Signal Processing Magazine,
"3D And Stereoscopic Visual Communication" May 1999, Vol. 16. No. 3.
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T. Jebara and A. Pentland.
"Action reaction learning: Automatic visual analysis and synthesis of
interactive behaviour". In International Conference on Vision Systems (ICVS), January 1999.
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B. Schiele, N. Oliver, T. Jebara and A. Pentland.
"An interactive computer vision system DyPERS: Dynamic personal enhanced reality system". In International Conference on Vision Systems (ICVS), January 1999.
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T. Choudhury, B. Clarkson, T. Jebara and A. Pentland.
"Multimodal person recognition using unconstrained audio and video". International Conference on Audio and VideoBased Biometric Person Authentication (AVBPA), 1999.
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1998
T. Jebara and A. Pentland.
"Maximum conditional likelihood via bound maximization and the CEM
algorithm". Neural Information Processing Systems 11 (NIPS), Dec. 1998.
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B. Moghaddam, T. Jebara and A. Pentland.
"Bayesian modeling of facial similarity". Neural Information Processing Systems 11 (NIPS), December 1998.
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T. Jebara, B. Schiele, N. Oliver and A. Pentland.
"DyPERS: Dynamic personal enhanced reality system".
In Proceedings of the 1998 Image Understanding Workshop, November 1998.
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T. Jebara.
Action reaction learning: Analysis and synthesis of human
behaviour . Master's Thesis, Media Laboratory, MIT, May 1998.
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T. Jebara, K. Russell and A. Pentland.
"Mixtures of eigenfeatures for realtime structure from texture" .
International Conference on Computer Vision (ICCV), January 1998.
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T. Jebara and A. Pentland.
"Action reaction learning: Analysis and synthesis of human behaviour". In Workshop on the Interpretation of
Visual Motion at the Conference on Computer
Vision and Pattern Recognition (CVPR), June 1998.
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T. Starner, B. Schiele, B. Rhodes, T. Jebara,
N. Oliver, J. Weaver and A. Pentland. "Augmented realities integrating
user and physical models". In Workshop on Augmented Reality, 1998.
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1997
T. Jebara, C. Eyster, J. Weaver, T. Starner and A. Pentland.
"Stochasticks: Augmenting the billiards experience with probabilistic vision and wearable computers".
International Symposium on Wearable Computers (ISWC), Oct. 1997.
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T. Jebara and A. Pentland.
"Parametrized structure from motion for 3D adaptive feedback tracking of faces".
Computer Vision and
Pattern Recognition (CVPR), June 1997.
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1996
T. Jebara.
3D pose estimation and normalization for face recognition . Undergraduate Thesis, Center for Intelligent
Machines, McGill University, May 1996.
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