Learn More
We propose, analyze and test an alternating minimization algorithm for recovering images from blurry and noisy observations with total variation (TV) regularization. This algorithm arises from a new half-quadratic model applicable to not only the anisotropic but also isotropic forms of total variation discretizations. The per-iteration computational(More)
In this paper, we propose and study the use of alternating direction algorithms for several 1-norm minimization problems arising from sparse solution recovery in compressive sensing, including the basis pursuit problem, the basis-pursuit denoising problems of both unconstrained and constrained forms, as well as others. We present and investigate two classes(More)
A matrix giving the traffic volumes between origin and destination in a network has tremendously potential utility for network capacity planning and management. Unfortunately, traffic matrices are generally unavailable in large operational IP networks. On the other hand, link load measurements are readily available in IP networks. In this paper, we propose(More)
We develop a general model to estimate the throughput and goodput between arbitrary pairs of nodes in the presence of interference from other nodes in a wireless network. Our model is based on measurements from the underlying network itself and is thus more accurate than abstract models of RF propagation such as those based on distance. The seed(More)
This work concerns primal-dual interior-point methods for semideenite programming (SDP) that use a search direction originally proposed by Helmberg-Rendl-Vanderbei-Wolkowicz 5] and Kojima-Shindoh-Hara 11], and recently rediscovered by Monteiro 15] in a more explicit form. In analyzing these methods, a number of basic equalities and inequalities were(More)
This paper considers the distribution of the rates at which flows transmit data, and the causes of these rates. First, using packet level traces from several Internet links, and summary flow statistics from an ISP backbone, we examine Internet flow rates and the relationship between the rate and other flow characteristics such as size and duration. We find,(More)
One widely-used technique by which network attackers attain anonymity and complicate their apprehension is by employing stepping stones: they launch attacks not from their own computer but from intermediary hosts that they previously compromised. We develop an efficient algorithm for detecting stepping stones by monitoring a site's Internet access link. The(More)
We consider solving minimization problems with 1-regularization: min x 1 + µf (x), particularly for f (x) = 1 2 Ax − b 2 M , where A ∈ R m×n and m < n. Our goal is to construct efficient and robust algorithms for solving large-scale problems with dense data, and our approach is based on two powerful algorithmic ideas: operator-splitting and continuation.(More)
We extend the alternating minimization algorithm recently proposed in [38, 39] to the case of recovering blurry multichannel (color) images corrupted by impulsive rather than Gaussian noise. The algorithm minimizes the sum of a multichannel extension of total variation (TV), either isotropic or anisotropic, and a data fidelity term measured in the L 1-norm.(More)
We present a unified analysis for a class of long-step primal-dual path-following algorithms for semidefinite programming whose search directions are obtained through linearization of the symmetrized equation of the central path Hp(XS)-[PXSP-~ + (PXSP 1)TI/2 = #I, introduced by Zhang. At an iterate (X, S), we choose a scaling matrix P from the class of(More)