搜索结果: 136-150 共查到“知识库 函数论”相关记录1419条 . 查询时间(3.089 秒)
An efficient method for large-scale slack allocation
timing graph slack allocation delay budgeting convex optimization truncated Newton method
2015/8/7
We consider a timing or project graph, with given delays on the edges and given arrival times at the source and sink nodes. We are to find the arrival times at the other nodes; these determine the tim...
Techniques for exploring the suboptimal set
Convex optimization Suboptimal set Support function Ellipsoidal approximations
2015/8/7
The epsilon-suboptimal set mathcal X_epsilon for an optimization problem is the set of feasible points with objective value within epsilon of optimal. In this paper we describe some basic techniques f...
Fast evaluation of quadratic control-Lyapunov policy
Quadratic lyapunov function quadratic programming the solution and optimization method computationally intensive control application
2015/8/7
The evaluation of a control-Lyapunov policy, with quadratic Lyapunov function, requires the solution of a quadratic program (QP) at each time step. For small problems this QP can be solved explicitly;...
Operation and configuration of a storage portfolio via convex optimization
Convex optimization Predictive control Energy management systems
2015/8/7
We consider a portfolio of storage devices which is used to modify a commodity flow so as to minimize an average cost function. The individual storage devices have different parameters that characteri...
Imputing a convex objective function
Optimization parameter optimization parameter function cost function
2015/8/7
We consider an optimizing process (or parametric optimization problem), i.e., an optimization problem that depends on some parameters. We present a method for imputing or estimating the objective func...
Min-max approximate dynamic programming
Dynamic planning policy dynamic system the noise the approximation function
2015/8/7
In this paper we describe an approximate dynamic programming policy for a discrete-time dynamical system perturbed by noise. The approximate value function is the pointwise supremum of a family of low...
Performance bounds and suboptimal policies for linear stochastic control via LMIs
dynamic programming stochastic control convex optimization
2015/8/7
In a recent paper, the authors showed how to compute performance bounds for infinite horizon stochastic control problems with linear system dynamics and arbitrary constraints, objective, and noise dis...
An ADMM algorithm for a class of total variation regularized estimation problems
Signal processing algorithms stochastic parameters parameter estimation convex optimization and regularization
2015/8/7
We present an alternating augmented Lagrangian method for convex optimization problems where the cost function is the sum of two terms, one that is separable in the variable blocks, and a second that ...
Accuracy at the top
Precision tao points function and convex agent convex optimization problem function hypothesis set
2015/8/7
We introduce a new notion of classification accuracy based on the top tau-quantile values of a scoring function, a relevant criterion in a number of problems arising for search engines. We de...
Iterated approximate value functions
The control strategy of function offline function optimization
2015/8/7
In this paper we introduce a control policy which we refer to as the iterated approximate value function policy. The generation of this policy requires two stages, the first one carried out off-line, ...
Maximizing a sum of sigmoids
Sigmoid function convex constraint set mathematics marketing network planning
2015/8/7
The problem of maximizing a sum of sigmoidal functions over a convex constraint set arises in many application areas. This objective captures the idea of decreasing marginal returns to investment, and...
Approximate dynamic programming via iterated Bellman inequalities
Convex Optimization Dynamic Programming Stochastic Control
2015/8/7
In this paper we introduce new methods for finding functions that lower bound the value function of a stochastic control problem, using an iterated form of the Bellman inequality. Our method is based ...
Proximal algorithms
Proximal algorithm optimization algorithm the standard tools smooth moderate scale high dimensional data set
2015/8/7
This monograph is about a class of optimization algorithms called proximal algorithms. Much like Newton's method is a standard tool for solving unconstrained smooth optimization problems of modest siz...
Extensions of Gauss quadrature via linear programming
Gauss quadrature Semi-infi nite programming Convex optimization
2015/8/7
Gauss quadrature is a well known method for estimating the integral of a continuous function with respect to a given measure as a weighted sum of the function evaluated at a set of node points. Gauss ...
Quadratic approximate dynamic programming for input-affine systems
approximate dynamic programming stochastic control convex optimization
2015/8/7
We consider the use of quadratic approximate value functions for stochastic control problems with input-affine dynamics and convex stage cost and constraints. Evaluating the approximate dynamic progra...