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Tree-Projected Gradient Descent for Estimating Gradient-Sparse Parameters on Graphs

May 31, 2020
Sheng Xu, Zhou Fan, Sahand Negahban


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Alternating Linear Bandits for Online Matrix-Factorization Recommendation

Oct 22, 2018
Hamid Dadkhahi, Sahand Negahban


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Deep supervised feature selection using Stochastic Gates

Oct 09, 2018
Yutaro Yamada, Ofir Lindenbaum, Sahand Negahban, Yuval Kluger


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Super-resolution estimation of cyclic arrival rates

Jun 05, 2018
Ningyuan Chen, Donald K. K. Lee, Sahand Negahban

* 31 pages, 5 figures 

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Minimax Estimation of Bandable Precision Matrices

Oct 19, 2017
Addison Hu, Sahand Negahban


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Restricted Strong Convexity Implies Weak Submodularity

Oct 12, 2017
Ethan R. Elenberg, Rajiv Khanna, Alexandros G. Dimakis, Sahand Negahban


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Learning from Comparisons and Choices

Apr 24, 2017
Sahand Negahban, Sewoong Oh, Kiran K. Thekumparampil, Jiaming Xu

* 64 pages, 4 figures. arXiv admin note: substantial text overlap with arXiv:1506.07947 

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Scalable Greedy Feature Selection via Weak Submodularity

Mar 08, 2017
Rajiv Khanna, Ethan Elenberg, Alexandros G. Dimakis, Sahand Negahban, Joydeep Ghosh

* To appear in AISTATS 2017 

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On Approximation Guarantees for Greedy Low Rank Optimization

Mar 08, 2017
Rajiv Khanna, Ethan Elenberg, Alexandros G. Dimakis, Sahand Negahban


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Understanding Adversarial Training: Increasing Local Stability of Neural Nets through Robust Optimization

Jan 16, 2016
Uri Shaham, Yutaro Yamada, Sahand Negahban


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Rank Centrality: Ranking from Pair-wise Comparisons

Nov 12, 2015
Sahand Negahban, Sewoong Oh, Devavrat Shah

* 45 pages, 3 figures 

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Scaling Multiple-Source Entity Resolution using Statistically Efficient Transfer Learning

Aug 09, 2012
Sahand Negahban, Benjamin I. P. Rubinstein, Jim Gemmell

* Short version to appear in CIKM'2012; 10 pages, 7 figures 

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Stochastic optimization and sparse statistical recovery: An optimal algorithm for high dimensions

Jul 18, 2012
Alekh Agarwal, Sahand Negahban, Martin J. Wainwright

* 2 figures 

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