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16th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)

作者： Delibaltov, Diana L. Ghosh, Pratim Rodoplu, Volkan Veeman, Michael Smith, William Manjunath, B. S. Univ Calif Santa Barbara Dept Elect & Comp Engn Santa Barbara CA 93106 USA Univ Calif Santa Barbara Dept Mol Cellular & Dev Santa Barbara CA 93106 USA Kansas State Univ Div Biol Manhattan KS 66506 USA

ISBN: (纸本)9783642408113;9783642408106

We address the problem of cell segmentation in confocal microscopy membrane volumes of the ascidian Ciona used in the study of morphogenesis. The primary challenges are non-uniform and patchy membrane staining and faint spurious boundaries from other organelles (e.g. nuclei). Traditional segmentation methods incorrectly attach to faint boundaries producing spurious edges. To address this problem, we propose a linear optimization framework for the joint correction of multiple over-segmentations obtained from different methods. The main idea motivating this approach is that multiple over-segmentations, resulting from a pool of methods with various parameters, are likely to agree on the correct segment boundaries, while spurious boundaries are method- or parameter-dependent. The challenge is to make an optimized decision on selecting the correct boundaries while discarding the spurious ones. The proposed unsupervised method achieves better performance than state of the art methods for cell segmentation from membrane images.

关键词： Cell segmentation linear program Joint segmentation

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A linear program to model daily car touring choices

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ANNALS OF TOURISM RESEARCH 2000年第2期27卷 451-467页

作者： Taplin, JHE McGinley, C Univ Western Australia Dept Informat Management & Mkt Perth WA 6907 Australia

A multi-period linear program is used to model daily decisions by Western Australian car tourists, subject to limits on average daily driving distance and the requirement that each journey starts and finishes at Perth within available vacation time. Varying weights or values are attached to going to multiple destinations and to warmer climates. Resulting choice patterns approximate to actual sequences of day-to-day choices by car tourists. A weighted sum of linear programming models provides a synthesized distribution of trips is similar to trip patterns revealed by survey data. This offers an insight into the factors and constraints influencing tourist decisions. (C) 2000 Elsevier Science Ltd. All rights reserved.

关键词： car tourists attractions linear program destination choice time constraints tourist goals multiple destinations

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SqueezeFit linear program: Fast and Robust Label-awareDimensionality Reduction

SqueezeFit Linear Program: Fast and Robust Label-awareDimens...

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作者： Lu, Tien-hsin The Ohio State University

学位级别：硕士

We introduce the SqueezeFit linear program as a fast and robust dimensionality reductionmethod. This program is inspired by both the SqueezeFit semi-definite program [10] andscGeneFit [3], which is a linear program version of SqueezeFit that has been used to classifysingle cell RNA-sequence data with a given structured partition. The original SqueezeFitsemi-definite program has a strong theoretical background but it exhibits slow runtimes withlarge data sets. In contrast, scGeneFit performs efficiently and robustly with scRNA-seqdata given either flat or hierarchical label partitions, but it does not have much theoreticaljustification for its performance. The SqueezeFit linear program fills this computational andtheoretical gap. After providing new theoretical guarantees, we illustrate the performanceof the SqueezeFit linear program on real-world gene expression data.

关键词： Mathematics Dimensionality reduction linear program marker gene selection machine learning mathematical data science optimization

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Reformulation of a linear program to Reduce the Average Current in a Modular Multilevel Converter

Reformulation of a Linear Program to Reduce the Average Curr...

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IEEE International Conference on Power and Energy Systems (ICPES)

作者： Nikola Petranovic Chris Townsend Tyrone Fernando Herbert Iu Electrical Electronic and Computer Engineering The University of Western Australia Crawley Australia

ISBN: (数字)9781728126586

ISBN: (纸本)9781728126593

A modular multilevel converter contains many capacitor full-bridge converter cells. An increased capacitance in the converter means a large overall converter size and increased converter cost. Previous research has investigated methods to reduce converter cell capacitance. One paper presents an iterative linear program to reduce the capacitance while limiting the average currents. The work presented in this paper modifies the linear program to further reduce average currents for similar reduction in capacitance. Furthermore, the results presented here show root-mean-square currents will also be reduced.

关键词： Modular multilevel converter optimisation linear program capacitor energy variation average current linear programming average current Capacitors multistage converter Converters capacitance

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Robust Phase Retrieval by Alternating Minimization

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2025年 73卷 40-54页

作者： Kim, Seonho Lee, Kiryung Ohio State Univ Dept ECE Columbus OH 43210 USA

We consider a least absolute deviation (LAD) approach to the robust phase retrieval problem that aims to recover a signal from its absolute measurements corrupted with sparse noise. To solve the resulting non-convex optimization problem, we propose a robust alternating minimization (Robust-AM) derived as an unconstrained Gauss-Newton method. To solve the inner optimization arising in each step of Robust-AM, we adopt two computationally efficient methods. We provide a non-asymptotic convergence analysis of these practical algorithms for Robust-AM under the standard Gaussian measurement assumption. These algorithms, when suitably initialized, are guaranteed to converge linearly to the ground truth at an order-optimal sample complexity with high probability while the support of sparse noise is arbitrarily fixed and the sparsity level is no larger than 1/4. Additionally, through comprehensive numerical experiments on synthetic and image datasets, we show that Robust-AM outperforms existing methods for robust phase retrieval offering comparable theoretical performance guarantees.

关键词： Optimization Signal processing algorithms Computational efficiency Minimization Extraterrestrial measurements Convergence Phase measurement Noise Computational modeling Vectors Phase retrieval outliers least absolute deviation linear program convex optimization

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LP-Rounding Based Algorithm for Capacitated Uniform Facility Location Problem with Soft Penalties

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Tsinghua Science and Technology 2025年第1期30卷 279-289页

作者： Runjie Miao Chenchen Wu Jinjiang Yuan School of Mathematics and Statistics Zhengzhou UniversityZhengzhou 450001China Institute of Operations Research and Systems Engineering Tianjin University of TechnologyTianjin 300384China

Capacitated facility location problem(CFLP)is a classical combinatorial optimization problem that has various applications in operations research,theoretical computer science,and management *** the CFLP,we have a potential facilities set and a clients *** facility has a certain capacity and an open cost,and each client has a spliitable demand that need to be *** goal is to open some facilities and assign all clients to these open facilities so that the total cost is as low as *** CFLP is NP-hard(non-deterministic polynomial-hard),and a large amount of work has been devoted to designing approximation algorithms for CFLP and its *** this vein,we introduce a new variant of CFLP called capacitated uniform facility location problem with soft penalties(CUFLPSP),in which the demand of each client can be partially rejected by paying penalty *** a result,we present a linear programming-rounding(LP-rounding)based 5.5122-approximation algorithm for the CUFLPSP.

关键词： capacitated facility location problem approximation algorithm soft penalties linear program

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Stochastic arbitrage with market index options

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JOURNAL OF BANKING & FINANCE 2025年 173卷

作者： Beare, Brendan K. Seo, Juwon Zheng, Zhongxi Univ Sydney Sch Econ Sydney NSW 2006 Australia Natl Univ Singapore Dept Econ Singapore 119077 Singapore

Opportunities for stochastic arbitrage in an options market arise when it is possible to construct a portfolio of options which provides a positive option premium and which, when combined with a direct investment in the underlying asset, generates a payoff which stochastically dominates the payoff from the direct investment in the underlying asset. We provide linear and mixed-integer linear programs for computing the stochastic arbitrage opportunity providing the maximum option premium to an investor. We apply our programs to 18 years of data on monthly put and call options on the Standard & Poors 500 index, finding no evidence that stochastic arbitrage opportunities are systematically present. A skewed specification of the underlying market return distribution with a constant market risk premium and constant multiplicative variance risk premium is broadly consistent with the pricing of market index options at moderate strikes.

关键词： linear program Mixed-integer linear program Option mispricing Portfolio choice Pricing kernel puzzle Stochastic arbitrage Stochastic dominance

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linear programMING AND CONSTRAINED AVERAGE OPTIMALITY FOR GENERAL CONTINUOUS-TIME MARKOV DECISION PROCESSES IN HISTORY-DEPENDENT POLICIES

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SIAM JOURNAL ON CONTROL AND OPTIMIZATION 2012年第1期50卷 23-47页

作者： Guo, Xianping Huang, Yonghui Song, Xinyuan Sun Yat Sen Univ Sch Math & Computat Sci Guangzhou 510275 Guangdong Peoples R China Chinese Univ Hong Kong Dept Stat Shatin Hong Kong Peoples R China

This paper attempts to study the constrained average optimality for continuous-time Markov decision processes in the class of randomized history-dependent policies. The states and actions are in general Polish spaces, and the transition rates are allowed to be unbounded. The optimality criterion to be optimized is expected average costs, multiple constraints are imposed on similar expected average costs, and all costs may be unbounded from above and from below. Under suitable conditions, we first show the existence of a constrained optimal policy by improving the concept of a stable policy in the previous literature and using the analogue of the forward Kolmogorov equation. Then, we develop a linear program (LP), which is equivalent to the constrained optimality problem and is used to obtain a constrained optimal policy. By introducing suitable operators and conditions, we further establish the dual program (DP) of the LP, show that the LP and DP are solvable, and show that there is no duality gap between them. Finally, we use a cash flow model and a controlled birth and death system to illustrate the applications of our main results.

关键词： continuous-time Markov decision process unbounded transition rate average criterion linear program constrained optimal policy

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linear programS WITH CONJUNCTIVE DATABASE QUERIES

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LOGICAL METHODS IN COMPUTER SCIENCE 2024年第1期20卷 9:1-9:48页

作者： Capelli, Florent Crosetti, Nicolas Niehren, Joachim Ramon, Jan Univ Lille Lille France INRIA Lille France

In this paper, we study the problem of optimizing a linear program whose variables are the answers to a conjunctive query. For this we propose the language LP(CQ) for specifying linear programs whose constraints and objective functions depend on the answer sets of conjunctive queries. We contribute an efficient algorithm for solving programs in a fragment of LP(CQ). The natural approach constructs a linear program having as many variables as there are elements in the answer set of the queries. Our approach constructs a linear program having the same optimal value but fewer variables. This is done by exploiting the structure of the conjunctive queries using generalized hypertree decompositions of small width to factorize elements of the answer set together. We illustrate the various applications of LP(CQ) programs on three examples: optimizing deliveries of resources, minimizing noise for differential privacy, and computing the s -measure of patterns in graphs as needed for data mining.

关键词： Database linear program optimization

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A simple SLP algorithm for solving a class of nonlinear programs

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 1997年第1期101卷 140-154页

作者： Sarker, RA Gunn, EA BANGLADESH UNIV ENGN & TECHNOL DEPT IND & PROT ENGNDHAKA 1000BANGLADESH TECH UNIV NOVA SCOTIA DEPT IND ENGNHALIFAXNS B3J 2X4CANADA

Successive linear programming (SLP) algorithms solve nonlinear optimization problems via a sequence of linear programs. We present an approach for a special class of nonlinear programming problems, which arise in multiperiod coal blending. The class of nonlinear programming problems and the solution approach considered in this paper are quite different from previous work. The algorithm is very simple, easy to apply and can be applied to as large a problem as the linear programming code can handle. The quality of solution, produced by the proposed algorithm, is discussed and the results of some test problems, in the real world environment, are provided. (C) 1997 Elsevier Science B.V.

关键词： linear program nonlinear program successive linear programming optimization feasibility optimality algorithm heuristic multiperiod coal blending

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