#### Filter Results:

- Full text PDF available (109)

#### Publication Year

1998

2018

- This year (13)
- Last 5 years (60)
- Last 10 years (142)

#### Publication Type

#### Co-author

#### Journals and Conferences

Learn More

- David L. Donoho, Arian Maleki, Andrea Montanari
- Proceedings of the National Academy of Sciences…
- 2009

Compressed sensing aims to undersample certain high-dimensional signals yet accurately reconstruct them by exploiting signal characteristics. Accurate reconstruction is possible when the object to be… (More)

- Mohsen Bayati, Andrea Montanari
- IEEE Transactions on Information Theory
- 2010

“Approximate message passing” (AMP) algorithms have proved to be effective in reconstructing sparse signals from a small number of incoherent linear measurements. Extensive numerical experiments… (More)

Given a matrix M of low-rank, we consider the problem of reconstructing it from noisy observations of a small, random subset of its entries. The problem arises in a variety of applications, from… (More)

- 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 of… (More)

- David L. Donoho, Arian Maleki, Andrea Montanari
- 2010 IEEE Information Theory Workshop on…
- 2010

In a recent paper, the authors proposed a new class of low-complexity iterative thresholding algorithms for reconstructing sparse signals from a small set of linear measurements. The new algorithms… (More)

- Andrea Montanari
- ArXiv
- 2010

This paper surveys recent work in applying ideas from graphical models and message passing algorithms to solve large scale regularized regression problems. In particular, the focus is on compressed… (More)

- David L. Donoho, Arian Maleki, Andrea Montanari
- IEEE Transactions on Information Theory
- 2011

Consider the noisy underdetermined system of linear equations: y = Ax<sub>0</sub> + z, with A an n × N measurement matrix, n <; N, and z ~ N(0, σ<sup>2</sup>I) a Gaussian white noise. Both y and A… (More)

Accurate Prediction of Phase Transitions in Compressed Sensing via a Connection to Minimax Denoising

- David L. Donoho, Iain Johnstone, Andrea Montanari
- IEEE Transactions on Information Theory
- 2013

Compressed sensing posits that, within limits, one can undersample a sparse signal and yet reconstruct it accurately. Knowing the precise limits to such undersampling is important both for theory and… (More)

- Florent Krzakala, Andrea Montanari, Federico Ricci-Tersenghi, Guilhem Semerjian, Lenka Zdeborová
- Proceedings of the National Academy of Sciences…
- 2007

An instance of a random constraint satisfaction problem defines a random subset (the set of solutions) of a large product space chiN (the set of assignments). We consider two prototypical problem… (More)