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- Adel Javanmard, Andrea Montanari
- Journal of Machine Learning Research
- 2014

Fitting high-dimensional statistical models often requires the use of non-linear parameter estimation procedures. As a consequence, it is generally impossible to obtain an exact characterization ofâ€¦ (More)

- David L. Donoho, Adel Javanmard, Andrea Montanari
- IEEE Trans. Information Theory
- 2013

- Mohammad Alizadeh, Adel Javanmard, Balaji Prabhakar
- SIGMETRICS
- 2011

Cloud computing, social networking and information networks (for search, news feeds, etc) are driving interest in the deployment of large data centers. TCP is the dominant Layer 3 transport protocolâ€¦ (More)

- Adel Javanmard, Andrea Montanari
- IEEE Transactions on Information Theory
- 2014

We consider linear regression in the high-dimensional regime where the number of observations n is smaller than the number of parameters p. A very successful approach in this setting usesâ€¦ (More)

- Adel Javanmard, Andrea Montanari
- ArXiv
- 2012

We consider a class of approximated message passing (AMP) algorithms and characterize their high-dimensional behavior in terms of a suitable state evolution recursion. Our proof applies to Gaussianâ€¦ (More)

This work considers the problem of learning linear Bayesian networks when some of the variables are unobserved. Identifiability and efficient recovery from low-order observable moments areâ€¦ (More)

- G. Hosein Mohimani, Farid Ashtiani, Adel Javanmard, Maziyar Hamdi
- IEEE Transactions on Vehicular Technology
- 2009

The mobility pattern of users is one of the distinct features of vehicular ad hoc networks (VANETs) compared with other types of mobile ad hoc networks (MANETs). This is due to the higher speed andâ€¦ (More)

- Adel Javanmard, Andrea Montanari, Federico Ricci-Tersenghi
- Proceedings of the National Academy of Sciencesâ€¦
- 2016

Statistical inference problems arising within signal processing, data mining, and machine learning naturally give rise to hard combinatorial optimization problems. These problems become intractableâ€¦ (More)

- Mahdi Soltanolkotabi, Adel Javanmard, Jason D. Lee
- ArXiv
- 2017

In this paper we study the problem of learning a shallow artificial neural network that best fits a training data set. We study this problem in the over-parameterized regime where the number ofâ€¦ (More)

- Adel Javanmard, Andrea Montanari
- ArXiv
- 2016

Multiple hypothesis testing is a core problem in statistical inference and arises in almost every scientific field. Given a set of null hypotheses H(n) = (H1, . . . ,Hn), Benjamini and Hochbergâ€¦ (More)