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2017第十届“大规模系统开发管理”国际会议（2017 Tenth International Conference "Management of Large-Scale System Development" (MLSD)）
2017 第十届 大规模系统开发管理 国际会议
2017/9/14
International Conference «Management of large-scale system development»(MLSD) is cross-disciplinary forum of academicians, researchers, teachers and practicians. Since 2007 Conferen...
Children of War:The Long-Run Effects of Large-Scale Physical Destruction and Warfare on Children
Children of War Long-Run Large-Scale Physical Destruction Warfare Children
2016/3/3
This paper provides causal evidence on the long-term consequences of large-scale physical destruction on educational attainment, health status, and labor market outcomes of children. I exploit the pla...
An Interior-Point Method for Large-Scale l1-Regularized Logistic Regression
logistic regression feature selection regularization regularization path
2015/7/10
Logistic regression with l1 regularization has been proposed as a promising method for feature selection in classification problems. In this paper we describe an efficient interior-point method for so...
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...
We consider the problem of choosing the gate sizes or scale factors in a combinational logic circuit in order to minimize the total area, subject to simple RC timing constraints, and a minimum allowed...
An Efficient Method for Large-scale Slack Allocation
timing graph, slack allocation delay budgeting convex optimization
2015/7/9
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...
Block Splitting for Large-Scale Distributed Learning
Block Splitting Large-Scale Distributed Learning
2015/7/9
Machine learning and statistics with very large datasets is now a topic of widespread interest, both in academia and industry. Many such tasks can be posed as convex optimization problems, so algorith...
User’s Guide for SNOPT Version 7: Software for Large-Scale Nonlinear Programming
optimization large-scale nonlinear programming nonlinear constraints
2015/7/3
SNOPT is a general-purpose system for constrained optimization. It minimizes a
linear or nonlinear function subject to bounds on the variables and sparse linear or
nonlinear constraints. It is suita...
SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization
large-scale optimization nonlinear programming
2015/7/3
Sequential quadratic programming (SQP) methods have proved highly effective for solving constrained optimization problems with smooth nonlinear functions in the objective
and constraints.Here w...
Stable and efficient updates to the basis matrix factors are vital to the simplex
method. The "best" updating method depends on the machine in use and how the update is implemented. For example, the ...
LARGE-SCALE LINEARLY CONSTRAINED OPTIMIZATION
Large-scale Systems Linear Constraints Linear Programming
2015/7/3
An algorithm for solving large-scale nonlinear' programs with linear constraints is presented.
The method combines efficient sparse-matrix techniques as in the revised simplex method
with stable q...
Evaluating the Effects of Large-Scale Health Interventions in Developing Countries:The Zambian Malaria Initiative
Cost vs Benefits Developing Countries and Economies Health Care and Treatment
2015/4/23
Since 2003, Zambia has been engaged in a large-scale, centrally coordinated national anti-malaria campaign which has become a model in sub-Saharan Africa. This paper aims at quantifying the individual...
Optimal Periodic Sensor Scheduling in Large-Scale Dynamical Networks
Dynamic system state estimation sensor scheduling sparsity sensor networks
2013/6/14
We consider the problem of finding optimal time-periodic sensor schedules for estimating the state of a large-scale dynamical system. We assume that a large number of sensors have been deployed and th...
Quantile Regression for Large-scale Applications
Quantile Regression Large-scale Applications
2013/6/14
Quantile regression is a method to estimate the quantiles of the conditional distribution of a response variable, and as such it permits a much more accurate portrayal of the relationship between the ...
Detecting Events and Patterns in Large-Scale User Generated Textual Streams with Statistical Learning Methods
Detecting Events Patterns Large-Scale User Generated Textual Streams Statistical Learning Methods
2012/9/18
A vast amount of textual web streams is influenced by events or phenomena emerging in the real world. The social web forms an excellent modern paradigm, where unstructured user generated content is pu...