

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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SUPPLEMENT 1 
SUPPLEMENT 2
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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BIB
N. Ruozzi and T. Jebara, "Making pairwise binary graphical models attractive" . Neural Information Processing Systems (NIPS), 2014.
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BIB
A. Weller and T. Jebara, "Approximating
the Bethe partition function" . Uncertainty in Artificial Intelligence (UAI), 2014.
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CODE
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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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CODE
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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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A. Weller.
"Methods for Inference in Graphical Models" .
PhD Thesis, Columbia University, 2014.
PDF
A. Choromanska.
"Selected Machine Learning Reductions" .
PhD Thesis, Columbia University, 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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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. "$\propto$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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T. Jebara.
"Perfect Graphs and Graphical Modeling" .
To Appear in
Tractability: Practical Approaches to Hard Problems,
Edited by Lucas Bordeaux, Youssef Hamadi, Pushmeet Kohli, and Robert Mateescu, Cambridge University Press, 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, December 2012.
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Y. Song.
"A Behaviorbased Approach Towards StatisticsPreserving Network Trace Anonymization" .
PhD Thesis, Columbia University, 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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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.
PDF  BIB  SLIDES  CODE  VIDEO
B. Huang. "Learning with DegreeBased Subgraph Estimation" .
PhD Thesis, Columbia University, 2011.
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B. Shaw. "Graph Embedding and Nonlinear Dimensionality Reduction" .
PhD Thesis, Columbia University, 2011.
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2010
P. Shivaswamy and T. Jebara.
"Laplacian Spectrum Learning" .
European Conference on Machine Learning (ECML), 2010.
PDF  BIB  SLIDES
P. Shivaswamy and T. Jebara.
"Empirical Bernstein Boosting" .
Thirteenth International Conference on Artificial Intelligence and Statistics, AISTATs, May 2010.
PDF  BIB  SLIDES  VIDEO
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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P. Shivaswamy. "Large Relative Margin and Applications" .
PhD Thesis, Columbia University, 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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SLIDES 
VIDEO
B. Shaw and T. Jebara.
"Structure Preserving Embedding" .
International Conference on Machine Learning, ICML, June 2009.
BEST PAPER AWARD
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SLIDES

VIDEO
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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SLIDES 
VIDEO
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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A. Howard and T. Jebara.
"Large Margin Transformation Learning" .
To appear in Journal of Machine Learning Research (JMLR), 2009. Preliminary version awaiting corrections for photoready.
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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.
PDF  BIB
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.
PDF  BIB
A. Howard. "Large Margin Transformation Learning" .
PhD Thesis, Columbia University, 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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BIB
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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BIB
B. Shaw and T. Jebara.
"Visualizing Graphs with Structure Preserving Embedding" .
Analyzing Graphs: Theory and Applications, NIPS Workshop. December 2008
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BIB
W. Jiang, S.F. Chang, T. Jebara and A.C. Loui.
"Semantic Concept Classification by Joint SemiSupervised Learning of Feature Subspaces and Support Vector Machiness" .
European Conference on Computer Vision, ECCV, October 2008.
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T. Jebara.
"Bayesian OutTrees" .
Uncertainty in Artificial Intelligence, UAI, July 2008.
PS 
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BIB
T. Jebara.
"OutTree Dependent Nonparametric Bayesian Inference"
.
Workshop on Nonparameteric Bayes, July 2008.
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BIB
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" .
Snowbird Machine Learning Workshop, April 2008.
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R. Kondor.
"Group theoretical methods in machine learning" .
PhD Thesis, Columbia University, May 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, NIPS, December 2007.
PS 
PDF 
BIB  Addendum
A. Howard and T. Jebara.
"Learning Monotonic Transformations for Classification" .
Neural Information Processing Systems, 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.
PDF  BIB  CODE
B. Shaw and T. Jebara.
"Minimum Volume Embedding" .
Artificial Intelligence and Statistics, AISTATS, March 2007.
PDF  BIB  CODE
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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Addendum on computing the kernelized Minimum Volume Ellipsoid
PS
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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.
PS  PDF  BIB  CODE
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" .
Learning Workshop, 2007.
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2006
R. Kondor and T. Jebara. "Gaussian and Wishart Hyperkernels" .
In Neural
Information Processing Systems (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 (NIPS), December 2006.
PDF  BIB
T. Jebara and V. Shchogolev.
"BMatching for Spectral Clustering" .
European Conference on Machine Learning, ECML, September 2006.
PDF  BIB
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.
HTML  PS  PDF  BIB
P. Shivaswamy and T. Jebara.
"Permutation Invariant SVMs" .
International Conference on Machine Learning, ICML, June 2006.
PS  PDF  BIB
D. Lewis, T. Jebara and W. Noble.
"NonStationary Kernel Combination" .
International Conference on Machine Learning, ICML, June 2006.
PDF  BIB
T. Jebara, B. Shaw and V. Shchogolev.
"BMatching for Embedding" .
Snowbird Machine Learning Conference, April 2006.
PDF  BIB
D. Lewis.
"Combining Kernels for Classification" .
PhD Thesis, Columbia University, May 2006.
PDF  BIB
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.
PS  PDF  BIB
T. Jebara and P. Long.
"Tree Dependent Identically Distributed Learning" .
Columbia University, Computer Science Technical Report, CUCS05005. 2005.
PS  PDF  BIB
A. Howard and T. Jebara.
"Square Root Propagation" .
Columbia University, Computer Science Technical Report, CUCS04005. 2005.
PS  PDF  BIB
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. HTML  PS 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. PS  PDF  BIB
A. Howard and T. Jebara. "Dynamical Systems Strees"
.
Uncertainty in Artificial Intelligence, UAI, July 2004.
PS  PDF  BIB
T. Jebara. "Kernelizing Sorting, Permutation and Alignment for Minimum Volume PCA"
.
Conference on Learning Theory, COLT, July 2004.
PS
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T. Jebara. "MultiTask Feature and Kernel Selection for SVMs"
.
International Conference on Machine Learning, ICML, July 2004.
PS
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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.
PDF  BIB
T. Jebara, and Y. Bengio. "Orbit Learning using Convex Optimization" . Snowbird Machine Learning, April 2004.
PS
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R. Kondor, T. Jebara, G. Csanyi, S. Ahnert. "Learning from Derivatives and other Linear Functionals" . Snowbird Machine Learning, April 2004.
HTML  PS
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2003
T. Jebara. Machine Learning: Discriminative and Generative .
Kluwer. ISBN 1402076479.
HTML  PS
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T. Jebara. "Images as Bags of Pixels" .
International Conference on Computer Vision, ICCV 2003.
PS 
PDF  BIB
T. Jebara and R. Kondor. "Bhattacharyya and Expected Likelihood Kernels" .
Conference on Learning Theory, COLT/KW 2003.
PS  PDF  BIB
A. Smola and R. Kondor. "Kernels and Regularization on Graphs" .
Conference on Learning Theory, COLT/KW 2003.
PS  PDF  BIB
R. Kondor and T. Jebara. "A Kernel Between Sets of Vectors" .
International Conference on Machine Learning, ICML 2003.
PS  PDF  BIB
T. Jebara and A. Howard. "Dynamical Systems Trees" .
Columbia University, Computer Science Technical Report, CUCS02803.
PS  PDF  BIB
T. Jebara. "Convex Invariance Learning" .
Artificial Intelligence and Statistics, AISTAT 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'02, June 2002.
PS  PDF  BIB
T. Jebara and T. Jaakkola. "MultiTask SVM
Feature Selection" .
Snowbird Machine Learning Workshop, 2002.
PDF  BIB  TALK
A. Kundaje, O. Antar, T. Jebara and C. Leslie.
"Learning Regulatory Networks from Sparsely Sampled Time Series
Expression Data" . Technical Report, 2002.
PDF  BIB
R.I. Kondor and J. Lafferty.
"Diffusion Kernels on Graphs and Other Discrete Input Spaces" . International Conference on Machine Learning (ICML), 2002.
PS  PDF  BIB
A. Honig, A. Howard, E. Eskin, and S. Stolfo.
" An Architecture for the Deployment of Data Miningbased
Intrusion Detection Systems." . Applications
of Data Mining in Computer Security. Kluwer 2002.
PS  PDF  BIB
2001
B. Schiele, T. Jebara, and N. Oliver. "Sensory
Augmented Computing: Wearing the Museum's Guide" .
IEEE Micro 21 (3),
May 2001.
PS  PDF  BIB
T. Jebara. "Discriminative, Generative and Imitative Learning" .
PhD Thesis, Media Laboratory, MIT, December 2001.
PS  PDF  BIB
2000
T. Jebara, and A. Pentland. "On Reversing Jensen's Inequality" .
In Neural
Information Processing Systems 13, NIPS 13. December 2000.
PS  PDF  BIB
B. Moghaddam, T. Jebara, and A. Pentland. "Bayesian Face Recognition" .
Pattern Recognition, Vol 33, Issue 11, pps 17711782. November 2000.
PDF  BIB
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.
PS  PDF  BIB
A. Pentland, T. Jebara, B. Clarkson and S. Basu. "Learning Techniques in Audiovisual Information Processing" .
In 15th International Conference on Pattern Recognition, ICPR 15 TUTORIAL. September 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
2000. July 2000.
HTML 
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1999
T. Jaakkola, M. Meila and T. Jebara. "Maximum Entropy Discrimination" . In Neural
Information Processing Systems 12, NIPS 12. December 1999.
PS 
PDF  BIB
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'99, August 1999.
PS 
PDF  BIB
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.
HTML 
PS 
PDF 
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.
PS 
PDF  BIB
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.
PS 
PDF  BIB
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.
PS 
PDF  BIB
1998
T. Jebara and A. Pentland.
"Maximum Conditional Likelihood via Bound Maximization and the CEM
Algorithm". In Neural Information Processing Systems 11, NIPS, Dec. 1998.
PS  PDF 
B. Moghaddam, T. Jebara and A. Pentland.
"Bayesian Modeling of Facial Similarity". In Neural Information Processing Systems 11,
NIPS, Dec. 1998.
PS 
PDF  BIB
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.

PS 
PDF 
T. Jebara, K. Russell and A. Pentland.
"Mixtures of Eigenfeatures for RealTime Structure from Texture" .
International Conference on Computer Vision (ICCV), January 1998.
PS 
PDF  BIB  Talk
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.
PS 
PDF  BIB
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.
PS 
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T. Jebara.
"Action Reaction Learning: Analysis and Synthesis of Human
Behaviour" . Master's Thesis, Media Laboratory, MIT, May 1998.
HTML 
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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.
HTML 
PS 
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T. Jebara and A. Pentland.
"Parametrized Structure from Motion for 3D Adaptive Feedback Tracking of Faces".
In IEEE Conference on Computer Vision and
Pattern Recognition, CVPR, June 1997.
PS 
PDF 
1996
T. Jebara.
"3D Pose Estimation and Normalization for Face Recognition" . Undergraduate Thesis, Center for Intelligent
Machines, McGill University, May 1996.
HTML 
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