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In this talk I will give an overview of some major developments in convex optimization that have emerged over the last ten years or so. The basic idea is that convex problems are fundamentally tractab...
Convex loss minimization with l1 regularization has been proposed as a promising method for feature selection in classification (e.g., l1-regularized logistic regression) and regression (e.g., l1-regu...
The increasing processing capability of Multi-Processor Systems-on-Chips (MPSoCs) is leading to an increase in chip power dissipation, which in turn leads to significant increase in chip temperature. ...
With technology advances, the number of cores integrated on a chip and their speed of operation is increasing. This, in turn is leading to a significant increase in chip temperature. Temperature gradi...
CVXGEN is a software tool that takes a high level description of a convex optimization problem family, and automatically generates custom C code that compiles into a reliable, high speed solver for th...
This paper describes how PID controllers can be designed by optimizing performance subject to robustness constraints. The optimization problem is solved using convex-concave programming. The method ad...
We investigate the convex-concave procedure (CCP), a local heuristic that utilizes the tools of convex optimization to find local optima of difference of convex (DC) programming problems. The class of...
We introduce a convex optimization modeling framework that transforms a convex optimization problem expressed in a form natural and convenient for the user into an equivalent cone program in a way tha...
We introduce disciplined convex stochastic programming (DCSP), a modeling framework that can significantly lower the barrier for modelers to specify and solve convex stochastic optimization problems, ...
For linear systems with delays, we define a new class of Lyapunov-like functionals that may be used to prove stability. We also show how we may design a stabilizing (delayed) state feedback for delay ...
We show that control system design via classical loop shaping and singular value loop shaping can be formulated as a closed-loop convex problem. Consequently, loop shaping problems can be solved by ef...
Many problems in engineering analysis and design can be cast as convex optimization problems, often nonlinear and nondifferentiable. We give a high-level description of recently developed interior-poi...
We point out some connections between applications of semidefinite programming in control and in combinatorial optimization. In both fields semidefinite programs arise as convex relaxations of NP-hard...
We show that a variety of antenna array pattern synthesis problems can be expressed as convex optimization problems, which can be (numerically) solved with great efficiency by recently developed inter...
We consider the design of finite impulse response (FIR) filters subject to upper and lower bounds on the frequency response magnitude. The associated optimization problems, with the filter coefficient...

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