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Learning Correlated Latent Representations with Adaptive Priors

Jul 16, 2019
Da Tang, Dawen Liang, Nicholas Ruozzi, Tony Jebara

* 12pages, 2 figures 

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A New Distribution on the Simplex with Auto-Encoding Applications

May 28, 2019
Andrew Stirn, Tony Jebara, David A Knowles

* 15 pages, 5 figures, 2 tables 

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Correlated Variational Auto-Encoders

May 16, 2019
Da Tang, Dawen Liang, Tony Jebara, Nicholas Ruozzi

* International Conference on Machine Learning (ICML), 2019 

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Beta Survival Models

May 09, 2019
David Hubbard, Benoit Rostykus, Yves Raimond, Tony Jebara

* 11 pages, 9 figures 

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Thompson Sampling for Noncompliant Bandits

Dec 03, 2018
Andrew Stirn, Tony Jebara

* 21 pages, 5 figures 

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Item Recommendation with Variational Autoencoders and Heterogenous Priors

Oct 07, 2018
Giannis Karamanolakis, Kevin Raji Cherian, Ananth Ravi Narayan, Jie Yuan, Da Tang, Tony Jebara

* Accepted for the 3rd Workshop on Deep Learning for Recommender Systems (DLRS 2018), held in conjunction with the 12th ACM Conference on Recommender Systems (RecSys 2018) in Vancouver, Canada 

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Subgoal Discovery for Hierarchical Dialogue Policy Learning

Sep 22, 2018
Da Tang, Xiujun Li, Jianfeng Gao, Chong Wang, Lihong Li, Tony Jebara

* 11 pages, 6 figures, EMNLP 2018 

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A refinement of Bennett's inequality with applications to portfolio optimization

Apr 16, 2018
Tony Jebara


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Variational Autoencoders for Collaborative Filtering

Feb 16, 2018
Dawen Liang, Rahul G. Krishnan, Matthew D. Hoffman, Tony Jebara

* 10 pages, 3 figures. WWW 2018 

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Initialization and Coordinate Optimization for Multi-way Matching

Mar 08, 2017
Da Tang, Tony Jebara

* Artificial Intelligence and Statistics (AISTATS), 2017 

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Frank-Wolfe Algorithms for Saddle Point Problems

Mar 03, 2017
Gauthier Gidel, Tony Jebara, Simon Lacoste-Julien

* Appears in: Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS 2017). 39 pages 

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Binary embeddings with structured hashed projections

Jul 01, 2016
Anna Choromanska, Krzysztof Choromanski, Mariusz Bojarski, Tony Jebara, Sanjiv Kumar, Yann LeCun

* arXiv admin note: text overlap with arXiv:1505.03190 

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Bethe Learning of Conditional Random Fields via MAP Decoding

Mar 04, 2015
Kui Tang, Nicholas Ruozzi, David Belanger, Tony Jebara

* 19 pages (9 supplementary), 10 figures (3 supplementary) 

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On Learning from Label Proportions

Feb 11, 2015
Felix X. Yu, Krzysztof Choromanski, Sanjiv Kumar, Tony Jebara, Shih-Fu Chang


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Semistochastic Quadratic Bound Methods

Feb 17, 2014
Aleksandr Y. Aravkin, Anna Choromanska, Tony Jebara, Dimitri Kanevsky

* 11 pages, 1 figure 

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Approximating the Bethe partition function

Dec 30, 2013
Adrian Weller, Tony Jebara


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Stochastic Bound Majorization

Sep 22, 2013
Anna Choromanska, Tony Jebara


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$\propto$SVM for learning with label proportions

Jun 04, 2013
Felix X. Yu, Dong Liu, Sanjiv Kumar, Tony Jebara, Shih-Fu Chang

* Appears in Proceedings of the 30th International Conference on Machine Learning (ICML 2013) 

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Bethe Bounds and Approximating the Global Optimum

Dec 31, 2012
Adrian Weller, Tony Jebara


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Approximating the Permanent with Belief Propagation

Aug 12, 2009
Bert Huang, Tony Jebara


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