Parametrized structure from motion for 3D adaptive feedback tracking of faces. - Tony Jebara; Alex Pentland (CVPR, 1997)

Stochasticks: Augmenting the Billiards Experience with Probabilistic Vision and Wearable Computers. - Tony Jebara; Cyrus Eyster; Joshua Weaver; Thad Starner; Alex Pentland (ISWC, 1997)

Mixtures of Eigen Features for Real-Time Structure from Texture. - Tony Jebara; Kenneth B. Russell; Alex Pentland (ICCV, 1998)

Efficient MAP/ML similarity matching for visual recognition. - Baback Moghaddam; Tony Jebara; Alex Pentland (ICPR, 1998)

Maximum Conditional Likelihood via Bound Maximization and the CEM Algorithm. - Tony Jebara; Alex Pentland (NIPS, 1998)

Bayesian Modeling of Facial Similarity. - Baback Moghaddam; Tony Jebara; Alex Pentland (NIPS, 1998)

Action Reaction Learning: Automatic Visual Analysis and Synthesis of Interactive Behaviour. - Tony Jebara; Alex Pentland (ICVS, 1999)

An Interactive Computer Vision System DyPERS: Dynamic Personal Enhanced Reality System. - Bernt Schiele; Nuria Oliver; Tony Jebara; Alex Pentland (ICVS, 1999)

Maximum Entropy Discrimination. - Tommi S. Jaakkola; Marina Meila; Tony Jebara (NIPS, 1999)

3D structure from 2D motion. - Tony Jebara; Ali Azarbayejani; Alex Pentland (IEEE Signal Process. Mag., 1999)

On Reversing Jensen's Inequality. - Tony Jebara; Alex Pentland (NIPS, 2000)

Feature Selection and Dualities in Maximum Entropy Discrimination. - Tony Jebara; Tommi S. Jaakkola (UAI, 2000)

Bayesian face recognition. - Baback Moghaddam; Tony Jebara; Alex Pentland (Pattern Recognit., 2000)

Convex Invariance Learning. - Tony Jebara (AISTATS, 2003)

Bhattacharyya Expected Likelihood Kernels. - Tony Jebara; Risi Kondor (COLT, 2003)

Images as Bags of Pixels. - Tony Jebara (ICCV, 2003)

A Kernel Between Sets of Vectors. - Risi Kondor; Tony Jebara (ICML, 2003)

Kernelizing Sorting, Permutation, and Alignment for Minimum Volume PCA. - Tony Jebara (COLT, 2004)

Multi-task feature and kernel selection for SVMs. - Tony Jebara (ICML, 2004)

An SVM Learning Approach to Robotic Grasping. - Raphael Pelossof; Andrew T. Miller; Peter K. Allen; Tony Jebara (ICRA, 2004)

Dynamical Systems Trees. - Andrew G. Howard; Tony Jebara (UAI, 2004)

Probability Product Kernels. - Tony Jebara; Risi Kondor; Andrew G. Howard (J. Mach. Learn. Res., 2004)

Clustered Blockwise PCA for Representing Visual Data. - Ko Nishino; Shree K. Nayar; Tony Jebara (IEEE Trans. Pattern Anal. Mach. Intell., 2005)

B-Matching for Spectral Clustering. - Tony Jebara; Vlad Shchogolev (ECML, 2006)

Nonstationary kernel combination. - Darrin P. Lewis; Tony Jebara; William Stafford Noble (ICML, 2006)

Permutation invariant SVMs. - Pannagadatta K. Shivaswamy; Tony Jebara (ICML, 2006)

Gaussian and Wishart Hyperkernels. - Risi Kondor; Tony Jebara (NIPS, 2006)

An EM Algorithm for Localizing Multiple Sound Sources in Reverberant Environments. - Michael I. Mandel; Daniel P. W. Ellis; Tony Jebara (NIPS, 2006)

Support vector machine learning from heterogeneous data: an empirical analysis using protein sequence and structure. - Darrin P. Lewis; Tony Jebara; William Stafford Noble (Bioinform., 2006)

Spectral Clustering and Embedding with Hidden Markov Models. - Tony Jebara; Yingbo Song; Kapil Thadani (ECML, 2007)

Learning Monotonic Transformations for Classification. - Andrew G. Howard; Tony Jebara (NIPS, 2007)

Density Estimation under Independent Similarly Distributed Sampling Assumptions. - Tony Jebara; Yingbo Song; Kapil Thadani (NIPS, 2007)

New trends in Cognitive Science: Integrative approaches to learning and development. - Gedeon O. Deák; Marni Stewart Bartlett; Tony Jebara (Neurocomputing, 2007)

Loopy Belief Propagation for Bipartite Maximum Weight b-Matching. - Bert Huang; Tony Jebara (AISTATS, 2007)

Multi-object tracking with representations of the symmetric group. - Risi Kondor; Andrew G. Howard; Tony Jebara (AISTATS, 2007)

Minimum Volume Embedding. - Blake Shaw; Tony Jebara (AISTATS, 2007)

Ellipsoidal Machines. - Pannagadatta K. Shivaswamy; Tony Jebara (AISTATS, 2007)

Semantic Concept Classification by Joint Semi-supervised Learning of Feature Subspaces and Support Vector Machines. - Wei Jiang 001; Shih-Fu Chang; Tony Jebara; Alexander C. Loui (ECCV (4), 2008)

Graph transduction via alternating minimization. - Jun Wang 006; Tony Jebara; Shih-Fu Chang (ICML, 2008)

Relative Margin Machines. - Pannagadatta K. Shivaswamy; Tony Jebara (NIPS, 2008)

Bayesian Out-Trees. - Tony Jebara (UAI, 2008)

Graph construction and b-matching for semi-supervised learning. - Tony Jebara; Jun Wang 006; Shih-Fu Chang (ICML, 2009)

Structure preserving embedding. - Blake Shaw; Tony Jebara (ICML, 2009)

Transformation Learning Via Kernel Alignment. - Andrew G. Howard; Tony Jebara (ICMLA, 2009)

Exact Graph Structure Estimation with Degree Priors. - Bert Huang; Tony Jebara (ICMLA, 2009)

Structured Prediction with Relative Margin. - Pannagadatta K. Shivaswamy; Tony Jebara (ICMLA, 2009)

Structured Prediction Models for Chord Transcription of Music Audio. - Adrian Weller; Daniel P. W. Ellis; Tony Jebara (ICMLA, 2009)

MAP Estimation, Message Passing, and Perfect Graphs. - Tony Jebara (UAI, 2009)

Approximating the Permanent with Belief Propagation - Bert Huang; Tony Jebara (CoRR, 2009)

Laplacian Spectrum Learning. - Pannagadatta K. Shivaswamy; Tony Jebara (ECML/PKDD (3), 2010)

Collaborative Filtering via Rating Concentration. - Bert Huang; Tony Jebara (AISTATS, 2010)

Maximum Relative Margin and Data-Dependent Regularization. - Pannagadatta K. Shivaswamy; Tony Jebara (J. Mach. Learn. Res., 2010)

Empirical Bernstein Boosting. - Pannagadatta K. Shivaswamy; Tony Jebara (AISTATS, 2010)

A markov routing algorithm for mobile DTNs based on spatio-temporal modeling of human movement data. - Arezu Moghadam; Tony Jebara; Henning Schulzrinne (MSWiM, 2011)

Learning a Distance Metric from a Network. - Blake Shaw; Bert Huang; Tony Jebara (NIPS, 2011)

Variance Penalizing AdaBoost. - Pannagadatta K. Shivaswamy; Tony Jebara (NIPS, 2011)

Fast b-matching via Sufficient Selection Belief Propagation. - Bert Huang; Tony Jebara (AISTATS, 2011)

Multitask Sparsity via Maximum Entropy Discrimination. - Tony Jebara (J. Mach. Learn. Res., 2011)

Majorization for CRFs and Latent Likelihoods. - Tony Jebara; Anna Choromanska (NIPS, 2012)

Bethe Bounds and Approximating the Global Optimum. - Adrian Weller; Tony Jebara (AISTATS, 2013)

Fast Spectral Clustering via the Nyström Method. - Anna Choromanska; Tony Jebara; Hyungtae Kim; Mahesh Mohan; Claire Monteleoni (ALT, 2013)

( propto )SVM for Learning with Label Proportions. - Felix X. Yu; Dong Liu 001; Sanjiv Kumar; Tony Jebara; Shih-Fu Chang (ICML (3), 2013)

Adaptive Anonymity via b-Matching. - Krzysztof Choromanski; Tony Jebara; Kui Tang (NIPS, 2013)

A multi-agent control framework for co-adaptation in brain-computer interfaces. - Josh Merel; Roy Fox; Tony Jebara; Liam Paninski (NIPS, 2013)

On MAP Inference by MWSS on Perfect Graphs. - Adrian Weller; Tony Jebara (UAI, 2013)

Stochastic Bound Majorization. - Anna Choromanska; Tony Jebara (CoRR, 2013)

Semi-supervised learning using greedy max-cut. - Jun Wang 006; Tony Jebara; Shih-Fu Chang (J. Mach. Learn. Res., 2013)

Perfect Graphs and Graphical Modeling. - Tony Jebara (Tractability, 2014)

Collaborative Ranking for Local Preferences. - Berk Kapicioglu; David S. Rosenberg; Robert E. Schapire; Tony Jebara (AISTATS, 2014)

Making Pairwise Binary Graphical Models Attractive. - Nicholas Ruozzi; Tony Jebara (NIPS, 2014)

Clamping Variables and Approximate Inference. - Adrian Weller; Tony Jebara (NIPS, 2014)

Approximating the Bethe Partition Function. - Adrian Weller; Tony Jebara (UAI, 2014)

Understanding the Bethe Approximation: When and How can it go Wrong? - Adrian Weller; Kui Tang; Tony Jebara; David A. Sontag (UAI, 2014)

Semistochastic Quadratic Bound Methods for Convex and Nonconvex Learning Problems. - Aleksandr Y. Aravkin; Anna Choromanska; Dimitri Kanevsky; Tony Jebara (ICLR (Workshop Poster), 2014)

On Learning with Label Proportions. - Felix X. Yu; Sanjiv Kumar; Tony Jebara; Shih-Fu Chang (CoRR, 2014)

Collaborative Place Models. - Berk Kapicioglu; David S. Rosenberg; Robert E. Schapire; Tony Jebara (IJCAI, 2015)

Coloring tournaments with forbidden substructures. - Krzysztof Choromanski; Tony Jebara (CoRR, 2015)

Bethe Learning of Conditional Random Fields via MAP Decoding. - Kui Tang; Nicholas Ruozzi; David Belanger 002; Tony Jebara (CoRR, 2015)

Bethe Learning of Graphical Models via MAP Decoding. - Kui Tang; Nicholas Ruozzi; David Belanger 002; Tony Jebara (AISTATS, 2016)

Binary embeddings with structured hashed projections. - Anna Choromanska; Krzysztof Choromanski; Mariusz Bojarski; Tony Jebara; Sanjiv Kumar; Yann LeCun (ICML, 2016)

Code relatives: detecting similarly behaving software. - Fang-Hsiang Su; Jonathan Bell 001; Kenneth Harvey; Simha Sethumadhavan; Gail E. Kaiser; Tony Jebara (SIGSOFT FSE, 2016)

Frank-Wolfe Algorithms for Saddle Point Problems. - Gauthier Gidel; Tony Jebara; Simon Lacoste-Julien (AISTATS, 2017)

Initialization and Coordinate Optimization for Multi-way Matching. - Da Tang; Tony Jebara (AISTATS, 2017)

A Privacy Analysis of Cross-device Tracking. - Sebastian Zimmeck; Jie S. Li; Hyungtae Kim; Steven M. Bellovin; Tony Jebara (USENIX Security Symposium, 2017)

Subgoal Discovery for Hierarchical Dialogue Policy Learning. - Da Tang; Xiujun Li; Jianfeng Gao 001; Chong Wang 002; Lihong Li 001; Tony Jebara (EMNLP, 2018)

Artwork personalization at netflix. - Fernando Amat Gil; Ashok Chandrashekar; Tony Jebara; Justin Basilico (RecSys, 2018)

Item Recommendation with Variational Autoencoders and Heterogeneous Priors. - Giannis Karamanolakis; Kevin Raji Cherian; Ananth Ravi Narayan; Jie Yuan; Da Tang; Tony Jebara (DLRS@RecSys, 2018)

Variational Autoencoders for Collaborative Filtering. - Dawen Liang; Rahul G. Krishnan; Matthew D. Hoffman; Tony Jebara (WWW, 2018)

A refinement of Bennett's inequality with applications to portfolio optimization. - Tony Jebara (CoRR, 2018)

Item Recommendation with Variational Autoencoders and Heterogenous Priors. - Giannis Karamanolakis; Kevin Raji Cherian; Ananth Ravi Narayan; Jie Yuan; Da Tang; Tony Jebara (CoRR, 2018)

Thompson Sampling for Noncompliant Bandits. - Andrew Stirn; Tony Jebara (CoRR, 2018)

Correlated Variational Auto-Encoders. - Da Tang; Dawen Liang; Tony Jebara; Nicholas Ruozzi (ICML, 2019)

On the Design of Estimators for Bandit Off-Policy Evaluation. - Nikos Vlassis; Aurélien Bibaut; Maria Dimakopoulou; Tony Jebara (ICML, 2019)

Marginal Posterior Sampling for Slate Bandits. - Maria Dimakopoulou; Nikos Vlassis; Tony Jebara (IJCAI, 2019)

A New Distribution on the Simplex with Auto-Encoding Applications. - Andrew Stirn; Tony Jebara; David A. Knowles (NeurIPS, 2019)

Variational low rank multinomials for collaborative filtering with side-information. - Ehtsham Elahi; Wei Wang; Dave Ray; Aish Fenton; Tony Jebara (RecSys, 2019)

Learning Correlated Latent Representations with Adaptive Priors. - Da Tang; Dawen Liang; Nicholas Ruozzi; Tony Jebara (CoRR, 2019)

ADMM SLIM: Sparse Recommendations for Many Users. - Harald Steck; Maria Dimakopoulou; Nickolai Riabov; Tony Jebara (WSDM, 2020)

Accordion: A Trainable Simulator forLong-Term Interactive Systems. - James McInerney; Ehtsham Elahi; Justin Basilico; Yves Raimond; Tony Jebara (RecSys, 2021)

Beta Survival Models. - David Hubbard; Benoit Rostykus; Yves Raimond; Tony Jebara (SPACA, 2021)

Active Multitask Learning with Committees. - Jingxi Xu 002; Da Tang; Tony Jebara (CoRR, 2021)

Multistate analysis with infinite mixtures of Markov chains. - Lucas Maystre; Tiffany Wu; Roberto Sanchis-Ojeda; Tony Jebara (UAI, 2022)

Using Survival Models to Estimate User Engagement in Online Experiments. - Praveen Chandar; Brian St. Thomas; Lucas Maystre; Vijay Pappu; Roberto Sanchis-Ojeda; Tiffany Wu; Ben Carterette; Mounia Lalmas; Tony Jebara (WWW, 2022)

Selectively Contextual Bandits. - Claudia V. Roberts; Maria Dimakopoulou; Qifeng Qiao; Ashok Chandrashekar; Tony Jebara (CoRR, 2022)

Calibrated Recommendations as a Minimum-Cost Flow Problem. - Himan Abdollahpouri; Zahra Nazari; Alex Gain; Clay Gibson; Maria Dimakopoulou; Jesse Anderton; Benjamin A. Carterette; Mounia Lalmas; Tony Jebara (WSDM, 2023)