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Sahand N. Negahban, Ph.D. - Publications

Affiliations: 
2012 Electrical Engineering & Computer Sciences University of California, Berkeley, Berkeley, CA, United States 
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15 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2019 Chen N, Lee DKK, Negahban SN. Super-resolution estimation of cyclic arrival rates Annals of Statistics. 47: 1754-1775. DOI: 10.1214/18-Aos1736  0.339
2018 Elenberg ER, Khanna R, Dimakis AG, Negahban SN. Restricted strong convexity implies weak submodularity Annals of Statistics. 46: 3539-3568. DOI: 10.1214/17-Aos1679  0.304
2018 Shaham U, Yamada Y, Negahban S. Understanding Adversarial Training: Increasing Local Stability of Neural Nets through Robust Optimization Neurocomputing. 307: 195-204. DOI: 10.1016/J.Neucom.2018.04.027  0.33
2017 Negahban S, Oh S, Shah D. Rank Centrality: Ranking from Pairwise Comparisons Operations Research. 65: 266-287. DOI: 10.1287/Opre.2016.1534  0.345
2014 Agarwal A, Negahban SN, Wainwright MJ. Stochastic optimization and sparse statistical recovery: An optimal algorithm for high dimensions 2014 48th Annual Conference On Information Sciences and Systems, Ciss 2014. DOI: 10.1109/CISS.2014.6814157  0.455
2013 Brink H, Richards JW, Poznanski D, Bloom JS, Rice J, Negahban S, Wainwright M. Using machine learning for discovery in synoptic survey imaging data Monthly Notices of the Royal Astronomical Society. 435: 1047-1060. DOI: 10.1093/Mnras/Stt1306  0.451
2012 Negahban SN, Ravikumar P, Wainwright MJ, Yu B. A unified framework for high-dimensional analysis of m-estimators with decomposable regularizers Statistical Science. 27: 538-557. DOI: 10.1214/12-Sts400  0.554
2012 Agarwal A, Negahban S, Wainwright MJ. Fast global convergence of gradient methods for high-dimensional statistical recovery Annals of Statistics. 40: 2452-2482. DOI: 10.1214/12-Aos1032  0.546
2012 Agarwal A, Negahban S, Wainwright MJ. Noisy matrix decomposition via convex relaxation: Optimal rates in high dimensions Annals of Statistics. 40: 1171-1197. DOI: 10.1214/12-Aos1000  0.578
2012 Agarwal A, Negahban S, Wainwright MJ. FASt global convergence of gradient methods for solving regularized M-estimation 2012 Ieee Statistical Signal Processing Workshop, Ssp 2012. 409-412. DOI: 10.1109/SSP.2012.6319717  0.426
2012 Agarwal A, Negahban SN, Wainwright MJ. Stochastic optimization and sparse statistical recovery: Optimal algorithms for high dimensions Advances in Neural Information Processing Systems. 2: 1538-1546.  0.455
2012 Negahban S, Wainwright MJ. Restricted strong convexity and weighted matrix completion: Optimal bounds with noise Journal of Machine Learning Research. 13: 1665-1697.  0.43
2011 Negahban SN, Wainwright MJ. Simultaneous support recovery in high dimensions: Benefits and perils of block ℓ 1/ℓ∞-regularization Ieee Transactions On Information Theory. 57: 3841-3863. DOI: 10.1109/TIT.2011.2144150  0.421
2010 Negahban S, Wainwright MJ. Estimation of (near) low-rank matrices with noise and high-dimensional scaling Icml 2010 - Proceedings, 27th International Conference On Machine Learning. 823-830. DOI: 10.1214/10-Aos850  0.555
2009 Negahban S, Wainwright MJ. Joint support recovery under high-dimensional scaling: Benefits and perils of ℓ 1,∞-regularization Advances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference. 1161-1168.  0.417
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