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Fundamental Tradeoffs in Distributionally Adversarial Training


Jan 15, 2021
Mohammad Mehrabi, Adel Javanmard, Ryan A. Rossi, Anup Rao, Tung Mai

* 23 pages, 3 figures 

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Near-Optimal Model Discrimination with Non-Disclosure


Dec 13, 2020
Dmitrii M. Ostrovskii, Mohamed Ndaoud, Adel Javanmard, Meisam Razaviyayn

* 49 pages, 2 figures; a few minor typos fixed 

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Precise Statistical Analysis of Classification Accuracies for Adversarial Training


Oct 21, 2020
Adel Javanmard, Mahdi Soltanolkotabi


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Dynamic Incentive-aware Learning: Robust Pricing in Contextual Auctions


Feb 25, 2020
Negin Golrezaei, Adel Javanmard, Vahab Mirrokni

* Accepted for publication in Operations Research Journal (An earlier version of this paper accepted to NeurIPS 2019.) 

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Precise Tradeoffs in Adversarial Training for Linear Regression


Feb 24, 2020
Adel Javanmard, Mahdi Soltanolkotabi, Hamed Hassani


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Online Debiasing for Adaptively Collected High-dimensional Data


Dec 18, 2019
Yash Deshpande, Adel Javanmard, Mohammad Mehrabi

* 64 pages, 2 tables, 8 figures; updated with minor fixes 

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New Computational and Statistical Aspects of Regularized Regression with Application to Rare Feature Selection and Aggregation


Apr 10, 2019
Amin Jalali, Adel Javanmard, Maryam Fazel


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Analysis of a Two-Layer Neural Network via Displacement Convexity


Jan 05, 2019
Adel Javanmard, Marco Mondelli, Andrea Montanari

* 54 pages, 11 pdf figures 

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Multi-Product Dynamic Pricing in High-Dimensions with Heterogenous Price Sensitivity


Jan 04, 2019
Adel Javanmard, Hamid Nazerzadeh, Simeng Shao

* 17 pages 

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Perturbation Bounds for Procrustes, Classical Scaling, and Trilateration, with Applications to Manifold Learning


Oct 22, 2018
Ery Arias-Castro, Adel Javanmard, Bruno Pelletier


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False Discovery Rate Control via Debiased Lasso


Mar 12, 2018
Adel Javanmard, Hamid Javadi

* 33 pages, 6 figures 

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Dynamic Pricing in High-dimensions


Jan 01, 2018
Adel Javanmard, Hamid Nazerzadeh

* 47 pages 

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Theoretical insights into the optimization landscape of over-parameterized shallow neural networks


Jul 16, 2017
Mahdi Soltanolkotabi, Adel Javanmard, Jason D. Lee


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Online Rules for Control of False Discovery Rate and False Discovery Exceedance


Jul 06, 2017
Adel Javanmard, Andrea Montanari

* 44 pages, 9 figures, to appear in Annals of Statistics 

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A Flexible Framework for Hypothesis Testing in High-dimensions


Apr 26, 2017
Adel Javanmard, Jason D. Lee

* 27 pages 

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Perishability of Data: Dynamic Pricing under Varying-Coefficient Models


Apr 24, 2017
Adel Javanmard

* 30 pages, 2 figures; accepted for publication in the Journal of Machine Learning Research (JMLR) 

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De-biasing the Lasso: Optimal Sample Size for Gaussian Designs


Jun 13, 2016
Adel Javanmard, Andrea Montanari

* 57 pages, 4 pdf figures (v3 contains stronger statement for unknown covariance, and several new applications) 

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Performance of a community detection algorithm based on semidefinite programming


Mar 30, 2016
Adel Javanmard, Andrea Montanari, Federico Ricci-Tersenghi

* J. Phys.: Conf. Ser. 699 (2016) 012015 
* 12 pages, 7 figures. Proceedings for the HD3-2015 conference (Kyoto, Dec 14-17, 2015) 

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On Online Control of False Discovery Rate


Mar 04, 2015
Adel Javanmard, Andrea Montanari

* 31 pages, 6 figures (minor edits) 

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1-Bit Matrix Completion under Exact Low-Rank Constraint


Feb 24, 2015
Sonia Bhaskar, Adel Javanmard

* 6 pages, 3 figures, to appear in CISS 2015 

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Confidence Intervals and Hypothesis Testing for High-Dimensional Regression


Apr 02, 2014
Adel Javanmard, Andrea Montanari

* 40 pages, 4 pdf figures 

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Hypothesis Testing in High-Dimensional Regression under the Gaussian Random Design Model: Asymptotic Theory


Feb 04, 2014
Adel Javanmard, Andrea Montanari

* 63 pages, 10 figures, 11 tables, Section 5 and Theorem 4.5 are added. Other modifications to improve presentation 

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Nearly Optimal Sample Size in Hypothesis Testing for High-Dimensional Regression


Nov 01, 2013
Adel Javanmard, Andrea Montanari

* 21 pages, short version appears in Annual Allerton Conference on Communication, Control and Computing, 2013 

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Learning Topic Models and Latent Bayesian Networks Under Expansion Constraints


May 24, 2013
Animashree Anandkumar, Daniel Hsu, Adel Javanmard, Sham M. Kakade

* 38 pages, 6 figures, 2 tables, applications in topic models and Bayesian networks are studied. Simulation section is added 

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Model Selection for High-Dimensional Regression under the Generalized Irrepresentability Condition


May 02, 2013
Adel Javanmard, Andrea Montanari

* 32 pages, 3 figures 

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Efficient Reinforcement Learning for High Dimensional Linear Quadratic Systems


Mar 24, 2013
Morteza Ibrahimi, Adel Javanmard, Benjamin Van Roy

* Advances in Neural Information Processing Systems (NIPS) 2012: 2645-2653 
* 16 pages 

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Localization from Incomplete Noisy Distance Measurements


Nov 21, 2012
Adel Javanmard, Andrea Montanari

* 46 pages, 8 figures, numerical experiments added. Journal version (v1,v2: Conference versions, ISIT 2011); Journal of Foundations of Computational Mathematics, 2012 

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Multi-track Map Matching


Sep 13, 2012
Adel Javanmard, Maya Haridasan, Li Zhang

* 11 pages, 8 figures, short version appears in 20th International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS 2012). Extended Abstract in Proceedings of the 10th international conference on Mobile systems, applications, and services (MobiSys 2012) 

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Robust Max-Product Belief Propagation


Nov 27, 2011
Morteza Ibrahimi, Adel Javanmard, Yashodhan Kanoria, Andrea Montanari

* 7 pages, 4 figures 

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