Tony Jebara

ORCID

Publication Activity (10 Years)

Years Active: 1997-2023
Publications (10 Years): 35

Top Venues

Publications

Himan Abdollahpouri, Zahra Nazari, Alex Gain, Clay Gibson, Maria Dimakopoulou, Jesse Anderton, Benjamin A. Carterette, Mounia Lalmas, Tony Jebara
Calibrated Recommendations as a Minimum-Cost Flow Problem. WSDM (2023)
Claudia V. Roberts, Maria Dimakopoulou, Qifeng Qiao, Ashok Chandrashekar, Tony Jebara
Selectively Contextual Bandits. CoRR (2022)
Praveen Chandar, Brian St. Thomas, Lucas Maystre, Vijay Pappu, Roberto Sanchis-Ojeda, Tiffany Wu, Ben Carterette, Mounia Lalmas, Tony Jebara
Using Survival Models to Estimate User Engagement in Online Experiments. WWW (2022)
Lucas Maystre, Tiffany Wu, Roberto Sanchis-Ojeda, Tony Jebara
Multistate analysis with infinite mixtures of Markov chains. UAI (2022)
James McInerney, Ehtsham Elahi, Justin Basilico, Yves Raimond, Tony Jebara
Accordion: A Trainable Simulator forLong-Term Interactive Systems. RecSys (2021)
Jingxi Xu, Da Tang, Tony Jebara
Active Multitask Learning with Committees. CoRR (2021)
David Hubbard, Benoit Rostykus, Yves Raimond, Tony Jebara
Beta Survival Models. SPACA (2021)
Harald Steck, Maria Dimakopoulou, Nickolai Riabov, Tony Jebara
ADMM SLIM: Sparse Recommendations for Many Users. WSDM (2020)
Da Tang, Dawen Liang, Nicholas Ruozzi, Tony Jebara
Learning Correlated Latent Representations with Adaptive Priors. CoRR (2019)
Ehtsham Elahi, Wei Wang, Dave Ray, Aish Fenton, Tony Jebara
Variational low rank multinomials for collaborative filtering with side-information. RecSys (2019)
Nikos Vlassis, Aurélien Bibaut, Maria Dimakopoulou, Tony Jebara
On the Design of Estimators for Bandit Off-Policy Evaluation. ICML (2019)
Andrew Stirn, Tony Jebara, David A. Knowles
A New Distribution on the Simplex with Auto-Encoding Applications. CoRR (2019)
Da Tang, Dawen Liang, Tony Jebara, Nicholas Ruozzi
Correlated Variational Auto-Encoders. ICML (2019)
David Hubbard, Benoit Rostykus, Yves Raimond, Tony Jebara
Beta Survival Models. CoRR (2019)
Da Tang, Dawen Liang, Tony Jebara, Nicholas Ruozzi
Correlated Variational Auto-Encoders. DGS@ICLR (2019)
Maria Dimakopoulou, Nikos Vlassis, Tony Jebara
Marginal Posterior Sampling for Slate Bandits. IJCAI (2019)
Andrew Stirn, Tony Jebara, David A. Knowles
A New Distribution on the Simplex with Auto-Encoding Applications. NeurIPS (2019)
Da Tang, Dawen Liang, Tony Jebara, Nicholas Ruozzi
Correlated Variational Auto-Encoders. CoRR (2019)
Da Tang, Xiujun Li, Jianfeng Gao, Chong Wang, Lihong Li, Tony Jebara
Subgoal Discovery for Hierarchical Dialogue Policy Learning. EMNLP (2018)
Giannis Karamanolakis, Kevin Raji Cherian, Ananth Ravi Narayan, Jie Yuan, Da Tang, Tony Jebara
Item Recommendation with Variational Autoencoders and Heterogeneous Priors. DLRS@RecSys (2018)
Da Tang, Xiujun Li, Jianfeng Gao, Chong Wang, Lihong Li, Tony Jebara
Subgoal Discovery for Hierarchical Dialogue Policy Learning. CoRR (2018)
Dawen Liang, Rahul G. Krishnan, Matthew D. Hoffman, Tony Jebara
Variational Autoencoders for Collaborative Filtering. CoRR (2018)
Andrew Stirn, Tony Jebara
Thompson Sampling for Noncompliant Bandits. CoRR (2018)
Dawen Liang, Rahul G. Krishnan, Matthew D. Hoffman, Tony Jebara
Variational Autoencoders for Collaborative Filtering. WWW (2018)
Fernando Amat Gil, Ashok Chandrashekar, Tony Jebara, Justin Basilico
Artwork personalization at netflix. RecSys (2018)
Giannis Karamanolakis, Kevin Raji Cherian, Ananth Ravi Narayan, Jie Yuan, Da Tang, Tony Jebara
Item Recommendation with Variational Autoencoders and Heterogenous Priors. CoRR (2018)
Tony Jebara
A refinement of Bennett's inequality with applications to portfolio optimization. CoRR (2018)
Sebastian Zimmeck, Jie S. Li, Hyungtae Kim, Steven M. Bellovin, Tony Jebara
A Privacy Analysis of Cross-device Tracking. USENIX Security Symposium (2017)
Da Tang, Tony Jebara
Initialization and Coordinate Optimization for Multi-way Matching. AISTATS (2017)
Gauthier Gidel, Tony Jebara, Simon Lacoste-Julien
Frank-Wolfe Algorithms for Saddle Point Problems. AISTATS (2017)
Da Tang, Tony Jebara
Initialization and Coordinate Optimization for Multi-way Matching. CoRR (2016)
Kui Tang, Nicholas Ruozzi, David Belanger, Tony Jebara
Bethe Learning of Graphical Models via MAP Decoding. AISTATS (2016)
Anna Choromanska, Krzysztof Choromanski, Mariusz Bojarski, Tony Jebara, Sanjiv Kumar, Yann LeCun
Binary embeddings with structured hashed projections. ICML (2016)
Fang-Hsiang Su, Jonathan Bell, Kenneth Harvey, Simha Sethumadhavan, Gail E. Kaiser, Tony Jebara
Code relatives: detecting similarly behaving software. SIGSOFT FSE (2016)
Gauthier Gidel, Tony Jebara, Simon Lacoste-Julien
Frank-Wolfe Algorithms for Saddle Point Problems. CoRR (2016)
Anna Choromanska, Krzysztof Choromanski, Mariusz Bojarski, Tony Jebara, Sanjiv Kumar, Yann LeCun
Binary embeddings with structured hashed projections. CoRR (2015)
Krzysztof Choromanski, Tony Jebara
Coloring tournaments with forbidden substructures. CoRR (2015)
Berk Kapicioglu, David S. Rosenberg, Robert E. Schapire, Tony Jebara
Collaborative Place Models. IJCAI (2015)
Kui Tang, Nicholas Ruozzi, David Belanger, Tony Jebara
Bethe Learning of Conditional Random Fields via MAP Decoding. CoRR (2015)
Adrian Weller, Tony Jebara
Approximating the Bethe partition function. CoRR (2014)
Adrian Weller, Tony Jebara
Clamping Variables and Approximate Inference. NIPS (2014)
Felix X. Yu, Sanjiv Kumar, Tony Jebara, Shih-Fu Chang
On Learning with Label Proportions. CoRR (2014)
Nicholas Ruozzi, Tony Jebara
Making Pairwise Binary Graphical Models Attractive. NIPS (2014)
Aleksandr Y. Aravkin, Anna Choromanska, Dimitri Kanevsky, Tony Jebara
Semistochastic Quadratic Bound Methods for Convex and Nonconvex Learning Problems. ICLR (Workshop Poster) (2014)
Adrian Weller, Tony Jebara
Approximating the Bethe Partition Function. UAI (2014)
Berk Kapicioglu, David S. Rosenberg, Robert E. Schapire, Tony Jebara
Collaborative Ranking for Local Preferences. AISTATS (2014)
Adrian Weller, Kui Tang, Tony Jebara, David A. Sontag
Understanding the Bethe Approximation: When and How can it go Wrong? UAI (2014)
Jun Wang, Tony Jebara, Shih-Fu Chang
Semi-supervised learning using greedy max-cut. J. Mach. Learn. Res. 14 (1) (2013)
Felix X. Yu, Dong Liu, Sanjiv Kumar, Tony Jebara, Shih-Fu Chang
$\propto$SVM for learning with label proportions. CoRR (2013)
Anna Choromanska, Tony Jebara
Stochastic Bound Majorization. CoRR (2013)
Adrian Weller, Tony Jebara
On MAP Inference by MWSS on Perfect Graphs. CoRR (2013)
Adrian Weller, Tony Jebara
On MAP Inference by MWSS on Perfect Graphs. UAI (2013)
Krzysztof Choromanski, Tony Jebara, Kui Tang
-Matching. NIPS (2013)
Tony Jebara, Tommi S. Jaakkola
Feature Selection and Dualities in Maximum Entropy Discrimination CoRR (2013)
Felix X. Yu, Dong Liu, Sanjiv Kumar, Tony Jebara, Shih-Fu Chang
$\propto$SVM for Learning with Label Proportions. ICML (3) (2013)
Adrian Weller, Tony Jebara
Bethe Bounds and Approximating the Global Optimum CoRR (2013)
Josh Merel, Roy Fox, Tony Jebara, Liam Paninski
A multi-agent control framework for co-adaptation in brain-computer interfaces. NIPS (2013)
Adrian Weller, Tony Jebara
Bethe Bounds and Approximating the Global Optimum. AISTATS (2013)
Anna Choromanska, Tony Jebara, Hyungtae Kim, Mahesh Mohan, Claire Monteleoni
Fast Spectral Clustering via the Nyström Method. ALT (2013)
Tony Jebara, Anna Choromanska
Majorization for CRFs and Latent Likelihoods. NIPS (2012)
Andrew G. Howard, Tony Jebara
Dynamical Systems Trees CoRR (2012)
Tony Jebara
MAP Estimation, Message Passing, and Perfect Graphs CoRR (2012)
Tony Jebara
Bayesian Out-Trees CoRR (2012)
Tony Jebara
Multitask Sparsity via Maximum Entropy Discrimination. J. Mach. Learn. Res. 12 (2011)
Pannagadatta K. Shivaswamy, Tony Jebara
Variance Penalizing AdaBoost. NIPS (2011)
Arezu Moghadam, Tony Jebara, Henning Schulzrinne
A markov routing algorithm for mobile DTNs based on spatio-temporal modeling of human movement data. MSWiM (2011)
Bert Huang, Tony Jebara
Fast b-matching via Sufficient Selection Belief Propagation. AISTATS (2011)
Blake Shaw, Bert Huang, Tony Jebara
Learning a Distance Metric from a Network. NIPS (2011)
Pannagadatta K. Shivaswamy, Tony Jebara
Laplacian Spectrum Learning. ECML/PKDD (3) (2010)
Pannagadatta K. Shivaswamy, Tony Jebara
Maximum Relative Margin and Data-Dependent Regularization. J. Mach. Learn. Res. 11 (2010)
Bert Huang, Tony Jebara
Collaborative Filtering via Rating Concentration. AISTATS (2010)
Pannagadatta K. Shivaswamy, Tony Jebara
Empirical Bernstein Boosting. AISTATS (2010)
Adrian Weller, Daniel P. W. Ellis, Tony Jebara
Structured Prediction Models for Chord Transcription of Music Audio. ICMLA (2009)
Blake Shaw, Tony Jebara
Structure preserving embedding. ICML (2009)
Tony Jebara, Jun Wang, Shih-Fu Chang
-matching for semi-supervised learning. ICML (2009)
Andrew G. Howard, Tony Jebara
Transformation Learning Via Kernel Alignment. ICMLA (2009)
Tony Jebara
MAP Estimation, Message Passing, and Perfect Graphs. UAI (2009)
Pannagadatta K. Shivaswamy, Tony Jebara
Structured Prediction with Relative Margin. ICMLA (2009)
Bert Huang, Tony Jebara
Approximating the Permanent with Belief Propagation CoRR (2009)
Bert Huang, Tony Jebara
Exact Graph Structure Estimation with Degree Priors. ICMLA (2009)
Pannagadatta K. Shivaswamy, Tony Jebara
Relative Margin Machines. NIPS (2008)
Tony Jebara
Bayesian Out-Trees. UAI (2008)
Wei Jiang, Shih-Fu Chang, Tony Jebara, Alexander C. Loui
Semantic Concept Classification by Joint Semi-supervised Learning of Feature Subspaces and Support Vector Machines. ECCV (4) (2008)
Jun Wang, Tony Jebara, Shih-Fu Chang
Graph transduction via alternating minimization. ICML (2008)
Tony Jebara, Yingbo Song, Kapil Thadani
Spectral Clustering and Embedding with Hidden Markov Models. ECML (2007)
Andrew G. Howard, Tony Jebara
Learning Monotonic Transformations for Classification. NIPS (2007)
Gedeon O. Deák, Marni Stewart Bartlett, Tony Jebara
New trends in Cognitive Science: Integrative approaches to learning and development. Neurocomputing 70 (13-15) (2007)
Risi Kondor, Andrew G. Howard, Tony Jebara
Multi-object tracking with representations of the symmetric group. AISTATS (2007)
Pannagadatta K. Shivaswamy, Tony Jebara
Ellipsoidal Machines. AISTATS (2007)
Blake Shaw, Tony Jebara
Minimum Volume Embedding. AISTATS (2007)
Tony Jebara, Yingbo Song, Kapil Thadani
Density Estimation under Independent Similarly Distributed Sampling Assumptions. NIPS (2007)
Bert Huang, Tony Jebara
Loopy Belief Propagation for Bipartite Maximum Weight b-Matching. AISTATS (2007)
Darrin P. Lewis, Tony Jebara, William Stafford Noble
Support vector machine learning from heterogeneous data: an empirical analysis using protein sequence and structure. Bioinform. 22 (22) (2006)
Darrin P. Lewis, Tony Jebara, William Stafford Noble
Nonstationary kernel combination. ICML (2006)
Tony Jebara, Vlad Shchogolev
B-Matching for Spectral Clustering. ECML (2006)
Michael I. Mandel, Daniel P. W. Ellis, Tony Jebara
An EM Algorithm for Localizing Multiple Sound Sources in Reverberant Environments. NIPS (2006)
Risi Kondor, Tony Jebara
Gaussian and Wishart Hyperkernels. NIPS (2006)
Pannagadatta K. Shivaswamy, Tony Jebara
Permutation invariant SVMs. ICML (2006)
Ko Nishino, Shree K. Nayar, Tony Jebara
Clustered Blockwise PCA for Representing Visual Data. IEEE Trans. Pattern Anal. Mach. Intell. 27 (10) (2005)
Tony Jebara, Risi Kondor, Andrew G. Howard
Probability Product Kernels. J. Mach. Learn. Res. 5 (2004)

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Publication Activity (10 Years)

Top Topics

Top Venues

Tony Jebara