Y.-M. Chen

Primer design through submodular function estimation

Y.-M. Chen, Yunheng Han, Ao wang, Aaron Hong et autres

MOTIVATION: Multiplex PCR-based enrichment is widely used in viral genome sequencing and pathogen surveillance. However, designing large sets of primers that maximize genome coverage while minimizing primer-primer interactions remains a major computational challenge. Existing methods such as SADDLE and Olivar use heuristics …

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Experimental Data, Scripts, and Results for Primer Design on Zika, FMDV, and SARS-CoV-2

Y.-M. Chen, YUNHENG HAN, Ao wang, A Ram Hong et autres

This item contains the experimental data, scripts, and results associated with the paper “Primer Design through Submodular Function Estimation.” The materials support the computational experiments conducted on Zika virus, foot-and-mouth disease virus (FMDV), and SARS-CoV-2 datasets. Included files provide the inputs, implementation …

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Experimental Data, Scripts, and Results for Primer Design on Zika, FMDV, and SARS-CoV-2

Y.-M. Chen, YUNHENG HAN, Ao wang, A Ram Hong et autres

This item contains the experimental data, scripts, and results associated with the paper “Primer Design through Submodular Function Estimation.” The materials support the computational experiments conducted on Zika virus, foot-and-mouth disease virus (FMDV), and SARS-CoV-2 datasets. Included files provide the inputs, implementation …

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Bicriteria Algorithms for Submodular Cover with Partition and Fairness Constraints

Wenjing Chen, Y.-M. Chen, Victoria G. Crawford

In many submodular optimization applications, datasets are naturally partitioned into disjoint subsets. These scenarios give rise to submodular optimization problems with partition-based constraints, where the desired solution set should be in some sense balanced, fair, or resource-constrained across these partitions. While existing …

Bicriteria Algorithms for Submodular Cover with Partition and Fairness Constraints

Wenjing Chen, Y.-M. Chen, Victoria G. Crawford

In many submodular optimization applications, datasets are naturally partitioned into disjoint subsets. These scenarios give rise to submodular optimization problems with partition-based constraints, where the desired solution set should be in some sense balanced, fair, or resource-constrained across these partitions. While existing …

Practical Submodular Maximization: A Primer

Y.-M. Chen, Alan Kuhnle

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Scalable Distributed Algorithms for Size-Constrained Submodular Maximization in the MapReduce and Adaptive Complexity Models

Y.-M. Chen, Tonmoy Dey, Alan Kuhnle

Distributed maximization of a submodular function in the MapReduce (MR) model has received much attention, culminating in two frameworks that allow a centralized algorithm to be run in the MR setting without loss of approximation, as long as the centralized algorithm satisfies …

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Practical and Parallelizable Algorithms for Non-Monotone Submodular Maximization with Size Constraint

Y.-M. Chen, Alan Kuhnle

We present combinatorial and parallelizable algorithms for the maximization of a submodular function, not necessarily monotone, with respect to a size constraint. We improve the best approximation factor achieved by an algorithm that has optimal adaptivity and nearly optimal query complexity to …

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Approximation Algorithms for Size-Constrained Non-Monotone Submodular Maximization in Deterministic Linear Time

Y.-M. Chen, Alan Kuhnle

In this work, we study the problem of finding the maximum value of a non-negative submodular function subject to a limit on the number of items selected, a ubiquitous problem that appears in many applications, such as data summarization and nonlinear regression. …

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Estimating two-dimensional angles of arrival in coherent source environment

Chi‐Chuan Yeh, Jaesung Lee, Y.-M. Chen

Estimating the two-dimensional (2-D) angle of arrival for radiating sources in a coherent environment is studied. The concept of spatial smoothing is first extended to a rectangular planar array, and a 2-D search function is formed to estimate the source directions. To …

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Calibration-free bearing estimation for arrays with randomly perturbed sensor locations

Y.-M. Chen, Jaesung Lee, Chi‐Chuan Yeh

Calibration-free bearing estimation algorithms for linearly periodic arrays with the presence of sensor positioning errors are investigated. The Toeplitz approximation method (TAM) is used to cope with the two-dimensional (2-D) sensor positioning errors which are assumed to be independent identically distributed and …

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Tissue-Type-Specific Heat-Shock Response and Immunolocalization of Class I Low-Molecular-Weight Heat-Shock Proteins in Soybean

Tsung-Luo Jinn, Pi‐Fang Linda Chang, Y.-M. Chen, Jaehong Key et autres

A monospecific polyclonal antibody was used to study the tissue-type specificity and intracellular localization of class I low-molecular-weight (LMW) heat-shock proteins (HSPs) in soybean (Glycine max) under different heat-shock regimes. In etiolated soybean seedlings, the root meristematic regions contained the highest levels …

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