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Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Some new algorithm developments on highly stiff stable schemes and on a SAV based approach for optimization problems
高刚性稳定方案 基于SAV 优化方法 新算法发展
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2023/11/29
In the first part, I shall present a new way to construct highly stiff stable schemes. Traditional time discretization schemes are usually based on Taylor expansions at $t_{n+\beta}$ with $\beta\in [0...
Stochastic Combinatorial Optimization via Poisson Approximation
Stochastic Knapsack Stochastic Bin Packing Expected Util- ity Maximization
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2016/1/23
We study several stochastic combinatorial problems, includ-ing the expected utility maximization problem, the stochas-tic knapsack problem and the stochastic bin packing prob-lem. A common technical c...
Approximating the Expected Values for Combinatorial Optimization Problems over Stochastic Points
Approximating Expected Values Combinatorial Optimization Problems Stochastic Points
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2016/1/22
We consider the stochastic geometry model where the location of each node is a random point in a given metric space,or the existence of each node is uncertain. We study the problem-s of computing the ...
Distributed optimization for cooperative agents: Application to formation flight
Distributed algorithm optimization communication dual duality
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2015/8/11
We present a simple decentralized algorithm to solve optimization problems involving cooperative agents. Cooperative agents share a common objective and simultaneously pursue private goals. Furthermor...
Network lasso: Clustering and optimization in large graphs
Convex Optimization ADMM Network Lasso
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2015/8/7
Convex optimization is an essential tool for modern data analysis, as it provides a framework to formulate and solve many problems in machine learning and data mining. However, general convex optimiza...
Optimization as an analysis tool for human complex decision making
mixed-integer programming nonlinear programming cognitive psychology measurement and performance
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2015/7/21
We present a problem class of mixed-integer nonlinear programs (MINLPs) with nonconvex continuous relaxations which stem from economic test scenarios that are used in the analysis of human complex pro...
Analysis and shape optimization in incompressible flows with unstructured grids
Adjoints Unstructured grids Incompressible fl ows
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2015/7/3
The reduced gradient evaluations provide major computa tional savings for unstructured grids and its accuracy and use for canonical and industrial problems is a major contribution of this study. The d...
Adjoint Formulations for Topology,Shape and Discrete Optimization
Adjoint Formulations Topology,Shape Discrete Optimization
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2015/7/2
The use of adjoints for PDE constrained optimization problems has become a common design tool in many areas of applied engineering. The use of adjoint methods for shape optimization has received much ...
Advanced Algorithms for Design and Optimization of Quiet Supersonic Platforms
Advanced Algorithms Design Optimization Quiet Supersonic Platforms
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2015/7/2
This paper describes the work carried out within the Stanford University group as part of the DARPA-funded Quiet Supersonic Platform (QSP) project. The objective of our work was to develop advanced nu...
Optimization-based Approximate Dynamic Programming
Approximate Dynamic Programming Approximate Linear Programming,
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2014/12/18
Reinforcement learning algorithms hold promise in many complex domains, such as resource management and planning under uncertainty. Most reinforcement learning algorithms are iterative - they successi...
Query-Time Optimization Techniques for Structured Queries in Information Retrieval
algorithms information retrieval optimization search
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2014/12/18
The use of information retrieval (IR) systems is evolving towards larger, more complicated queries. Both the IR industrial and research communities have generated significant evidence indicating that ...
Design of Non-Uniform Linear Array via Linear Programming and Particle Swarm Optimization and Studies on Phased Array Calibration
linear array linear programming particle swarm optimization side lobe level phased array calibration
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2014/12/8
For a linear array, the excitation coefficients of each element and its geometry play an important role, because they will determine the radiation pattern of the given array. Side Lobe Level (SLL) is ...
International Conference on Optimization, Sparsity and Adaptive Data Analysis
Optimization Sparsity Adaptive Data Analysis
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2014/10/20
The purpose of this international conference is to bring experts from different disciplines together to exchange ideas and identify new research opportunities in analyzing large scale data in which sp...
COMPARISON OF PARTICLE SWARM OPTIMIZATION AND GENETIC ALGORITHM IN RATIONAL FUNCTION MODEL OPTIMIZATION
Rational Function Model (RFM) Particle Swarm Optimization (PSO) Genetic Algorithm (GA) Mathematical Modelling High Resolution Satellite Images (HRSIs)
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2014/4/25
Rational Function Models (RFM) are one of the most considerable approaches for spatial information extraction from satellite images especially where there is no access to the sensor parameters. As the...
Sequence alignment from the perspective of stochastic optimization: a survey
Sequence alignment stochastic optimization simulated annealing genetic algorithms particle swarm optimization ant colonyoptimization
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2011/3/22
DNA and protein are the fundamental biological sequences. DNA is a fundamental molecule that plays a vital role in the processes of life. Proteins synthesized by DNA in a cell are the building blocks ...