Results 1 - 10 of 24,431

On the Optimal Power-Distortion Region for Asymmetric Gaussian Sensor Networks with Fading ∗

by Hamid Behroozi, Fady Alajaji, Tamás Linder , 2008
"... Abstract—We consider the estimation of a Gaussian source by a Gaussian sensor network where L distributed sensors transmit noisy observations of the source through a fading Gaussian multiple access channel (MAC) to a fusion center (FC). Since sensor power is usually limited, our goal is to character ..."
Abstract - Cited by 3 (2 self) - Add to MetaCart
and sufficient conditions for the achievability of (L +1)−tuples (P1,P2,...,PL,D). For a symmetric Gaussian sensor network with deterministic and equal-magnitude fading, we derive the optimal power-distortion tradeoff. We also provide an achievable power-distortion region for the asymmetric sensor network

SNOPT: An SQP Algorithm For Large-Scale Constrained Optimization

by Philip E. Gill, Walter Murray, Michael A. Saunders , 2002
"... Sequential quadratic programming (SQP) methods have proved highly effective for solving constrained optimization problems with smooth nonlinear functions in the objective and constraints. Here we consider problems with general inequality constraints (linear and nonlinear). We assume that first deriv ..."
Abstract - Cited by 597 (24 self) - Add to MetaCart
Sequential quadratic programming (SQP) methods have proved highly effective for solving constrained optimization problems with smooth nonlinear functions in the objective and constraints. Here we consider problems with general inequality constraints (linear and nonlinear). We assume that first

On the limited memory BFGS method for large scale optimization

by Dong C. Liu, Jorge Nocedal - MATHEMATICAL PROGRAMMING , 1989
"... ..."
Abstract - Cited by 780 (15 self) - Add to MetaCart
Abstract not found

A Data Locality Optimizing Algorithm

by Michael E. Wolf, Monica S. Lam , 1991
"... This paper proposes an algorithm that improves the locality of a loop nest by transforming the code via interchange, reversal, skewing and tiling. The loop transformation algorithm is based on two concepts: a mathematical formulation of reuse and locality, and a loop transformation theory that unifi ..."
Abstract - Cited by 804 (16 self) - Add to MetaCart
, and Givens QR factorization. Performance evaluation indicates that locality optimization is especially crucial for scaling up the performance of parallel code.

Making Large-Scale SVM Learning Practical

by Thorsten Joachims , 1998
"... Training a support vector machine (SVM) leads to a quadratic optimization problem with bound constraints and one linear equality constraint. Despite the fact that this type of problem is well understood, there are many issues to be considered in designing an SVM learner. In particular, for large lea ..."
Abstract - Cited by 1861 (17 self) - Add to MetaCart
Training a support vector machine (SVM) leads to a quadratic optimization problem with bound constraints and one linear equality constraint. Despite the fact that this type of problem is well understood, there are many issues to be considered in designing an SVM learner. In particular, for large

Automatically characterizing large scale program behavior

by Timothy Sherwood, Erez Perelman, Greg Hamerly , 2002
"... Understanding program behavior is at the foundation of computer architecture and program optimization. Many pro-grams have wildly different behavior on even the very largest of scales (over the complete execution of the program). This realization has ramifications for many architectural and com-pile ..."
Abstract - Cited by 778 (41 self) - Add to MetaCart
Understanding program behavior is at the foundation of computer architecture and program optimization. Many pro-grams have wildly different behavior on even the very largest of scales (over the complete execution of the program). This realization has ramifications for many architectural and com

Making Large-Scale Support Vector Machine Learning Practical

by Thorsten Joachims , 1998
"... Training a support vector machine (SVM) leads to a quadratic optimization problem with bound constraints and one linear equality constraint. Despite the fact that this type of problem is well understood, there are many issues to be considered in designing an SVM learner. In particular, for large lea ..."
Abstract - Cited by 628 (1 self) - Add to MetaCart
Training a support vector machine (SVM) leads to a quadratic optimization problem with bound constraints and one linear equality constraint. Despite the fact that this type of problem is well understood, there are many issues to be considered in designing an SVM learner. In particular, for large

Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones

by Jos F. Sturm , 1998
"... SeDuMi is an add-on for MATLAB, that lets you solve optimization problems with linear, quadratic and semidefiniteness constraints. It is possible to have complex valued data and variables in SeDuMi. Moreover, large scale optimization problems are solved efficiently, by exploiting sparsity. This pape ..."
Abstract - Cited by 1368 (5 self) - Add to MetaCart
SeDuMi is an add-on for MATLAB, that lets you solve optimization problems with linear, quadratic and semidefiniteness constraints. It is possible to have complex valued data and variables in SeDuMi. Moreover, large scale optimization problems are solved efficiently, by exploiting sparsity

Matched source-channel communication for field estimation in wireless sensor networks

by Waheed Bajwa - Proc. the Fouth Int. Symposium on Information Processing in Sensor Networks , 2005
"... Abstract — Sensing, processing and communication must be jointly optimized for efficient operation of resource-limited wireless sensor networks. We propose a novel source-channel matching approach for distributed field estimation that naturally integrates these basic operations and facilitates a uni ..."
Abstract - Cited by 40 (11 self) - Add to MetaCart
cell is implicitly computed at the destination via the coherent spatial averaging inherent in the MAC, resulting in optimal power-distortion scaling with the number

ATOMIC DECOMPOSITION BY BASIS PURSUIT

by Scott Shaobing Chen , David L. Donoho , Michael A. Saunders , 1995
"... The Time-Frequency and Time-Scale communities have recently developed a large number of overcomplete waveform dictionaries -- stationary wavelets, wavelet packets, cosine packets, chirplets, and warplets, to name a few. Decomposition into overcomplete systems is not unique, and several methods for d ..."
Abstract - Cited by 2728 (61 self) - Add to MetaCart
variation de-noising, and multi-scale edge denoising. Basis Pursuit in highly overcomplete dictionaries leads to large-scale optimization problems. With signals of length 8192 and a wavelet packet dictionary, one gets an equivalent linear program of size 8192 by 212,992. Such problems can be attacked
Results 1 - 10 of 24,431