Tony Jebara - RankMe

123 papers A* 23A 27B 2C 6Misc 1Journal 37Unranked 26

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Unified Language Model for Large Scale Search, Recommendation, and Reasoning. CoRR Marco De Nadai, Edoardo D'Amico, Max Lefarov, Alexandre Tamborrino, Divita Vohra, Mark VanMiddlesworth, Shawn Lin, Jacqueline Wood, Jan Stypka, Eliza Klyce, Keshi Dai, Timothy Christopher Heath, Martin D. Gould, Yves Raimond, Sandeep Ghael, Tony Jebara, Andreas Damianou, Vladan Radosavljevic, Paul N. Bennett, Mounia Lalmas, Praveen Chandar
2023	A	`conf`	Calibrated Recommendations as a Minimum-Cost Flow Problem. WSDM Himan Abdollahpouri, Zahra Nazari, Alex Gain, Clay Gibson, Maria Dimakopoulou, Jesse Anderton, Benjamin A. Carterette, Mounia Lalmas, Tony Jebara
2022	A	`conf`	Multistate analysis with infinite mixtures of Markov chains. UAI Lucas Maystre, Tiffany Wu, Roberto Sanchis-Ojeda, Tony Jebara
2022	J	`jnl`	Selectively Contextual Bandits. CoRR Claudia V. Roberts, Maria Dimakopoulou, Qifeng Qiao, Ashok Chandrashekar, Tony Jebara
2022	A*	`conf`	Using Survival Models to Estimate User Engagement in Online Experiments. WWW Praveen Chandar, Brian St. Thomas, Lucas Maystre, Vijay Pappu, Roberto Sanchis-Ojeda, Tiffany Wu, Ben Carterette, Mounia Lalmas, Tony Jebara
2021	A	`conf`	Accordion: A Trainable Simulator forLong-Term Interactive Systems. RecSys James McInerney, Ehtsham Elahi, Justin Basilico, Yves Raimond, Tony Jebara
2021	J	`jnl`	Active Multitask Learning with Committees. CoRR Jingxi Xu, Da Tang, Tony Jebara
2021	—	`conf`	Beta Survival Models. SPACA David Hubbard, Benoit Rostykus, Yves Raimond, Tony Jebara
2020	A	`conf`	ADMM SLIM: Sparse Recommendations for Many Users. WSDM Harald Steck, Maria Dimakopoulou, Nickolai Riabov, Tony Jebara
2019	A*	`conf`	A New Distribution on the Simplex with Auto-Encoding Applications. NeurIPS Andrew Stirn, Tony Jebara, David A. Knowles
2019	J	`jnl`	A New Distribution on the Simplex with Auto-Encoding Applications. CoRR Andrew Stirn, Tony Jebara, David A. Knowles
2019	J	`jnl`	Beta Survival Models. CoRR David Hubbard, Benoit Rostykus, Yves Raimond, Tony Jebara
2019	—	`conf`	Correlated Variational Auto-Encoders. DGS@ICLR Da Tang, Dawen Liang, Tony Jebara, Nicholas Ruozzi
2019	A*	`conf`	Correlated Variational Auto-Encoders. ICML Da Tang, Dawen Liang, Tony Jebara, Nicholas Ruozzi
2019	J	`jnl`	Correlated Variational Auto-Encoders. CoRR Da Tang, Dawen Liang, Tony Jebara, Nicholas Ruozzi
2019	J	`jnl`	Learning Correlated Latent Representations with Adaptive Priors. CoRR Da Tang, Dawen Liang, Nicholas Ruozzi, Tony Jebara
2019	A*	`conf`	Marginal Posterior Sampling for Slate Bandits. IJCAI Maria Dimakopoulou, Nikos Vlassis, Tony Jebara
2019	A*	`conf`	On the Design of Estimators for Bandit Off-Policy Evaluation. ICML Nikos Vlassis, Aurélien Bibaut, Maria Dimakopoulou, Tony Jebara
2019	A	`conf`	Variational low rank multinomials for collaborative filtering with side-information. RecSys Ehtsham Elahi, Wei Wang, Dave Ray, Aish Fenton, Tony Jebara
2018	J	`jnl`	A refinement of Bennett's inequality with applications to portfolio optimization. CoRR Tony Jebara
2018	A	`conf`	Artwork personalization at netflix. RecSys Fernando Amat Gil, Ashok Chandrashekar, Tony Jebara, Justin Basilico
2018	—	`conf`	Item Recommendation with Variational Autoencoders and Heterogeneous Priors. DLRS@RecSys Giannis Karamanolakis, Kevin Raji Cherian, Ananth Ravi Narayan, Jie Yuan, Da Tang, Tony Jebara
2018	J	`jnl`	Item Recommendation with Variational Autoencoders and Heterogenous Priors. CoRR Giannis Karamanolakis, Kevin Raji Cherian, Ananth Ravi Narayan, Jie Yuan, Da Tang, Tony Jebara
2018	A*	`conf`	Subgoal Discovery for Hierarchical Dialogue Policy Learning. EMNLP Da Tang, Xiujun Li, Jianfeng Gao, Chong Wang, Lihong Li, Tony Jebara
2018	J	`jnl`	Subgoal Discovery for Hierarchical Dialogue Policy Learning. CoRR Da Tang, Xiujun Li, Jianfeng Gao, Chong Wang, Lihong Li, Tony Jebara
2018	J	`jnl`	Thompson Sampling for Noncompliant Bandits. CoRR Andrew Stirn, Tony Jebara
2018	A*	`conf`	Variational Autoencoders for Collaborative Filtering. WWW Dawen Liang, Rahul G. Krishnan, Matthew D. Hoffman, Tony Jebara
2018	J	`jnl`	Variational Autoencoders for Collaborative Filtering. CoRR Dawen Liang, Rahul G. Krishnan, Matthew D. Hoffman, Tony Jebara
2017	A*	`conf`	A Privacy Analysis of Cross-device Tracking. USENIX Security Symposium Sebastian Zimmeck, Jie S. Li, HyungTae Kim, Steven M. Bellovin, Tony Jebara
2017	A	`conf`	Frank-Wolfe Algorithms for Saddle Point Problems. AISTATS Gauthier Gidel, Tony Jebara, Simon Lacoste-Julien
2017	A	`conf`	Initialization and Coordinate Optimization for Multi-way Matching. AISTATS Da Tang, Tony Jebara
2016	A	`conf`	Bethe Learning of Graphical Models via MAP Decoding. AISTATS Kui Tang, Nicholas Ruozzi, David Belanger, Tony Jebara
2016	A*	`conf`	Binary embeddings with structured hashed projections. ICML Anna Choromanska, Krzysztof Choromanski, Mariusz Bojarski, Tony Jebara, Sanjiv Kumar, Yann LeCun
2016	—	`conf`	Code relatives: detecting similarly behaving software. SIGSOFT FSE Fang-Hsiang Su, Jonathan Bell, Kenneth Harvey, Simha Sethumadhavan, Gail E. Kaiser, Tony Jebara
2016	J	`jnl`	Frank-Wolfe Algorithms for Saddle Point Problems. CoRR Gauthier Gidel, Tony Jebara, Simon Lacoste-Julien
2016	J	`jnl`	Initialization and Coordinate Optimization for Multi-way Matching. CoRR Da Tang, Tony Jebara
2015	J	`jnl`	Bethe Learning of Conditional Random Fields via MAP Decoding. CoRR Kui Tang, Nicholas Ruozzi, David Belanger, Tony Jebara
2015	J	`jnl`	Binary embeddings with structured hashed projections. CoRR Anna Choromanska, Krzysztof Choromanski, Mariusz Bojarski, Tony Jebara, Sanjiv Kumar, Yann LeCun
2015	A*	`conf`	Collaborative Place Models. IJCAI Berk Kapicioglu, David S. Rosenberg, Robert E. Schapire, Tony Jebara
2015	J	`jnl`	Coloring tournaments with forbidden substructures. CoRR Krzysztof Choromanski, Tony Jebara
2014	A	`conf`	Approximating the Bethe Partition Function. UAI Adrian Weller, Tony Jebara
2014	J	`jnl`	Approximating the Bethe partition function. CoRR Adrian Weller, Tony Jebara
2014	—	`conf`	Clamping Variables and Approximate Inference. NIPS Adrian Weller, Tony Jebara
2014	A	`conf`	Collaborative Ranking for Local Preferences. AISTATS Berk Kapicioglu, David S. Rosenberg, Robert E. Schapire, Tony Jebara
2014	—	`conf`	Making Pairwise Binary Graphical Models Attractive. NIPS Nicholas Ruozzi, Tony Jebara
2014	J	`jnl`	On Learning with Label Proportions. CoRR Felix X. Yu, Sanjiv Kumar, Tony Jebara, Shih-Fu Chang
2014	—	`ch.`	Perfect Graphs and Graphical Modeling. Tractability Tony Jebara
2014	—	`conf`	Semistochastic Quadratic Bound Methods for Convex and Nonconvex Learning Problems. ICLR (Workshop Poster) Aleksandr Y. Aravkin, Anna Choromanska, Dimitri Kanevsky, Tony Jebara
2014	A	`conf`	Understanding the Bethe Approximation: When and How can it go Wrong? UAI Adrian Weller, Kui Tang, Tony Jebara, David A. Sontag
2013	J	`jnl`	$\propto$SVM for learning with label proportions. CoRR Felix X. Yu, Dong Liu, Sanjiv Kumar, Tony Jebara, Shih-Fu Chang
2013	—	`conf`	A multi-agent control framework for co-adaptation in brain-computer interfaces. NIPS Josh Merel, Roy Fox, Tony Jebara, Liam Paninski
2013	—	`conf`	Adaptive Anonymity via NIPS Krzysztof Choromanski, Tony Jebara, Kui Tang
2013	J	`jnl`	Bethe Bounds and Approximating the Global Optimum CoRR Adrian Weller, Tony Jebara
2013	A	`conf`	Bethe Bounds and Approximating the Global Optimum. AISTATS Adrian Weller, Tony Jebara
2013	B	`conf`	Fast Spectral Clustering via the Nyström Method. ALT Anna Choromanska, Tony Jebara, HyungTae Kim, Mahesh Mohan, Claire Monteleoni
2013	J	`jnl`	Feature Selection and Dualities in Maximum Entropy Discrimination CoRR Tony Jebara, Tommi S. Jaakkola
2013	A	`conf`	On MAP Inference by MWSS on Perfect Graphs. UAI Adrian Weller, Tony Jebara
2013	J	`jnl`	On MAP Inference by MWSS on Perfect Graphs. CoRR Adrian Weller, Tony Jebara
2013	J	`jnl`	Semi-supervised learning using greedy max-cut. J. Mach. Learn. Res. Jun Wang, Tony Jebara, Shih-Fu Chang
2013	J	`jnl`	Stochastic Bound Majorization. CoRR Anna Choromanska, Tony Jebara
2013	—	`conf`	$\propto$SVM for Learning with Label Proportions. ICML (3) Felix X. Yu, Dong Liu, Sanjiv Kumar, Tony Jebara, Shih-Fu Chang
2012	J	`jnl`	Bayesian Out-Trees CoRR Tony Jebara
2012	J	`jnl`	Dynamical Systems Trees CoRR Andrew G. Howard, Tony Jebara
2012	J	`jnl`	MAP Estimation, Message Passing, and Perfect Graphs CoRR Tony Jebara
2012	—	`conf`	Majorization for CRFs and Latent Likelihoods. NIPS Tony Jebara, Anna Choromanska
2011	A	`conf`	A markov routing algorithm for mobile DTNs based on spatio-temporal modeling of human movement data. MSWiM Arezu Moghadam, Tony Jebara, Henning Schulzrinne
2011	A	`conf`	Fast b-matching via Sufficient Selection Belief Propagation. AISTATS Bert Huang, Tony Jebara
2011	—	`conf`	Learning a Distance Metric from a Network. NIPS Blake Shaw, Bert Huang, Tony Jebara
2011	J	`jnl`	Multitask Sparsity via Maximum Entropy Discrimination. J. Mach. Learn. Res. Tony Jebara
2011	—	`conf`	Variance Penalizing AdaBoost. NIPS Pannagadatta K. Shivaswamy, Tony Jebara
2010	A	`conf`	Collaborative Filtering via Rating Concentration. AISTATS Bert Huang, Tony Jebara
2010	A	`conf`	Empirical Bernstein Boosting. AISTATS Pannagadatta K. Shivaswamy, Tony Jebara
2010	—	`conf`	Laplacian Spectrum Learning. ECML/PKDD (3) Pannagadatta K. Shivaswamy, Tony Jebara
2010	J	`jnl`	Maximum Relative Margin and Data-Dependent Regularization. J. Mach. Learn. Res. Pannagadatta K. Shivaswamy, Tony Jebara
2009	J	`jnl`	Approximating the Permanent with Belief Propagation CoRR Bert Huang, Tony Jebara
2009	C	`conf`	Exact Graph Structure Estimation with Degree Priors. ICMLA Bert Huang, Tony Jebara
2009	A*	`conf`	Graph construction and ICML Tony Jebara, Jun Wang, Shih-Fu Chang
2009	A	`conf`	MAP Estimation, Message Passing, and Perfect Graphs. UAI Tony Jebara
2009	A*	`conf`	Structure preserving embedding. ICML Blake Shaw, Tony Jebara
2009	C	`conf`	Structured Prediction Models for Chord Transcription of Music Audio. ICMLA Adrian Weller, Daniel P. W. Ellis, Tony Jebara
2009	C	`conf`	Structured Prediction with Relative Margin. ICMLA Pannagadatta K. Shivaswamy, Tony Jebara
2009	C	`conf`	Transformation Learning Via Kernel Alignment. ICMLA Andrew G. Howard, Tony Jebara
2008	A	`conf`	Bayesian Out-Trees. UAI Tony Jebara
2008	A*	`conf`	Graph transduction via alternating minimization. ICML Jun Wang, Tony Jebara, Shih-Fu Chang
2008	—	`conf`	Relative Margin Machines. NIPS Pannagadatta K. Shivaswamy, Tony Jebara
2008	—	`conf`	Semantic Concept Classification by Joint Semi-supervised Learning of Feature Subspaces and Support Vector Machines. ECCV (4) Wei Jiang, Shih-Fu Chang, Tony Jebara, Alexander C. Loui
2007	—	`conf`	Density Estimation under Independent Similarly Distributed Sampling Assumptions. NIPS Tony Jebara, Yingbo Song, Kapil Thadani
2007	A	`conf`	Ellipsoidal Machines. AISTATS Pannagadatta K. Shivaswamy, Tony Jebara
2007	—	`conf`	Learning Monotonic Transformations for Classification. NIPS Andrew G. Howard, Tony Jebara
2007	A	`conf`	Loopy Belief Propagation for Bipartite Maximum Weight b-Matching. AISTATS Bert Huang, Tony Jebara
2007	A	`conf`	Minimum Volume Embedding. AISTATS Blake Shaw, Tony Jebara
2007	A	`conf`	Multi-object tracking with representations of the symmetric group. AISTATS Risi Kondor, Andrew G. Howard, Tony Jebara
2007	J	`jnl`	New trends in Cognitive Science: Integrative approaches to learning and development. Neurocomputing Gedeon O. Deák, Marni Stewart Bartlett, Tony Jebara
2007	—	`conf`	Spectral Clustering and Embedding with Hidden Markov Models. ECML Tony Jebara, Yingbo Song, Kapil Thadani
2006	—	`conf`	An EM Algorithm for Localizing Multiple Sound Sources in Reverberant Environments. NIPS Michael I. Mandel, Daniel P. W. Ellis, Tony Jebara
2006	—	`conf`	B-Matching for Spectral Clustering. ECML Tony Jebara, Vlad Shchogolev
2006	—	`conf`	Gaussian and Wishart Hyperkernels. NIPS Risi Kondor, Tony Jebara
2006	A*	`conf`	Nonstationary kernel combination. ICML Darrin P. Lewis, Tony Jebara, William Stafford Noble
2006	A*	`conf`	Permutation invariant SVMs. ICML Pannagadatta K. Shivaswamy, Tony Jebara
2006	J	`jnl`	Support vector machine learning from heterogeneous data: an empirical analysis using protein sequence and structure. Bioinform. Darrin P. Lewis, Tony Jebara, William Stafford Noble
2005	J	`jnl`	Clustered Blockwise PCA for Representing Visual Data. IEEE Trans. Pattern Anal. Mach. Intell. Ko Nishino, Shree K. Nayar, Tony Jebara
2004	A*	`conf`	An SVM Learning Approach to Robotic Grasping. ICRA Raphael Pelossof, Andrew T. Miller, Peter K. Allen, Tony Jebara
2004	A	`conf`	Dynamical Systems Trees. UAI Andrew G. Howard, Tony Jebara
2004	A*	`conf`	Kernelizing Sorting, Permutation, and Alignment for Minimum Volume PCA. COLT Tony Jebara
2004	A*	`conf`	Multi-task feature and kernel selection for SVMs. ICML Tony Jebara
2004	J	`jnl`	Probability Product Kernels. J. Mach. Learn. Res. Tony Jebara, Risi Kondor, Andrew G. Howard
2003	A*	`conf`	A Kernel Between Sets of Vectors. ICML Risi Kondor, Tony Jebara
2003	A*	`conf`	Bhattacharyya Expected Likelihood Kernels. COLT Tony Jebara, Risi Kondor
2003	A	`conf`	Convex Invariance Learning. AISTATS Tony Jebara
2003	A*	`conf`	Images as Bags of Pixels. ICCV Tony Jebara
2000	J	`jnl`	Bayesian face recognition. Pattern Recognit. Baback Moghaddam, Tony Jebara, Alex Pentland
2000	A	`conf`	Feature Selection and Dualities in Maximum Entropy Discrimination. UAI Tony Jebara, Tommi S. Jaakkola
2000	—	`conf`	On Reversing Jensen's Inequality. NIPS Tony Jebara, Alex Pentland
1999	J	`jnl`	3D structure from 2D motion. IEEE Signal Process. Mag. Tony Jebara, Ali Azarbayejani, Alex Pentland
1999	C	`conf`	Action Reaction Learning: Automatic Visual Analysis and Synthesis of Interactive Behaviour. ICVS Tony Jebara, Alex Pentland
1999	C	`conf`	An Interactive Computer Vision System DyPERS: Dynamic Personal Enhanced Reality System. ICVS Bernt Schiele, Nuria Oliver, Tony Jebara, Alex Pentland
1999	—	`conf`	Maximum Entropy Discrimination. NIPS Tommi S. Jaakkola, Marina Meila, Tony Jebara
1998	—	`conf`	Bayesian Modeling of Facial Similarity. NIPS Baback Moghaddam, Tony Jebara, Alex Pentland
1998	B	`conf`	Efficient MAP/ML similarity matching for visual recognition. ICPR Baback Moghaddam, Tony Jebara, Alex Pentland
1998	—	`conf`	Maximum Conditional Likelihood via Bound Maximization and the CEM Algorithm. NIPS Tony Jebara, Alex Pentland
1998	A*	`conf`	Mixtures of Eigen Features for Real-Time Structure from Texture. ICCV Tony Jebara, Kenneth B. Russell, Alex Pentland
1997	A*	`conf`	Parametrized structure from motion for 3D adaptive feedback tracking of faces. CVPR Tony Jebara, Alex Pentland
1997	Misc	`conf`	Stochasticks: Augmenting the Billiards Experience with Probabilistic Vision and Wearable Computers. ISWC Tony Jebara, Cyrus Eyster, Joshua Weaver, Thad Starner, Alex Pentland