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Policies for Simultaneous Estimation and Optimization
Policies Simultaneous Estimation Optimization
2015/7/10
Policies for the joint identification and control of uncertain systems are presented. The discussion focuses on the case of a multiple input, single output linear system, with no dynamics and quadrati...
Distributed Estimation via Dual Decomposition
Distributed Estimation via Dual Decomposition
2015/7/10
The focus of this paper is to develop a framework for distributed estimation via convex optimization. We deal with a network of complex sensor subsystems with local estimation and signal processing. M...
An Interior-Point Method for Large Scale Network Utility Maximization
An Interior-Point Method Large Scale Network Utility Maximization
2015/7/10
We describe a specialized truncated Newton primal-dual interior-point method that solves large scale network utility maximization problems, with concave utility functions, efficiently and reliably. Ou...
Graph Implementations for Nonsmooth Convex Programs
Convex optimization nonsmooth optimization optimization modeling languages semidefinite programming
2015/7/9
We describe graph implementations, a generic method for representing a convex function via its epigraph, described in a disciplined convex programming framework. This simple and natural idea allows a ...
Robust Beamforming via Worst-Case SINR Maximization
Beamforming convex optimization signal-to-interference-plus-noise ratio (SINR)
2015/7/9
Minimum variance beamforming, which uses a weight vector that maximizes the signal to interference plus noise ratio (SINR), is often sensitive to estimation error and uncertainty in the parameters, st...
A Minimax Theorem with Applications to Machine Learning, Signal Processing, and Finance
convex optimization minimax theorem robust optimization
2015/7/9
This paper concerns a fractional function of the form x^Ta/sqrt{x^TBx}, where B is positive definite. We consider the game of choosing x from a convex set, to maximize the function, and choosing (a,B)...
Linear Models Based on Noisy Data and the Frisch Scheme
linear models factor analysis identifi cation
2015/7/8
We address the problem of identifying linear relations among variables based on noisy measurements. This is a central question in the search for structure in large data sets. Often a key assumption is...