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Efficient Algorithms for Planning with Participation Constraints [article]

Hanrui Zhang, Yu Cheng, Vincent Conitzer
2022 arXiv   pre-print
We consider the problem of planning with participation constraints introduced in [Zhang et al., 2022]. In this problem, a principal chooses actions in a Markov decision process, resulting in separate utilities for the principal and the agent. However, the agent can and will choose to end the process whenever his expected onward utility becomes negative. The principal seeks to compute and commit to a policy that maximizes her expected utility, under the constraint that the agent should always
more » ... t to continue participating. We provide the first polynomial-time exact algorithm for this problem for finite-horizon settings, where previously only an additive ε-approximation algorithm was known. Our approach can also be extended to the (discounted) infinite-horizon case, for which we give an algorithm that runs in time polynomial in the size of the input and log(1/ε), and returns a policy that is optimal up to an additive error of ε.
arXiv:2205.07767v1 fatcat:z7kt2gioxfb3feim4dxhk52ssu

The Quantum Entropy Cone of Hypergraphs [article]

Ning Bao, Newton Cheng, Sergio Hernández-Cuenca, Vincent P. Su
2020 arXiv   pre-print
In this work, we generalize the graph-theoretic techniques used for the holographic entropy cone to study hypergraphs and their analogously-defined entropy cone. This allows us to develop a framework to efficiently compute entropies and prove inequalities satisfied by hypergraphs. In doing so, we discover a class of quantum entropy vectors which reach beyond those of holographic states and obey constraints intimately related to the ones obeyed by stabilizer states and linear ranks. We show
more » ... at least up to 4 parties, the hypergraph cone is identical to the stabilizer entropy cone, thus demonstrating that the hypergraph framework is broadly applicable to the study of entanglement entropy. We conjecture that this equality continues to hold for higher party numbers and report on partial progress on this direction. To physically motivate this conjectured equivalence, we also propose a plausible method inspired by tensor networks to construct a quantum state from a given hypergraph such that their entropy vectors match.
arXiv:2002.05317v1 fatcat:ggt653s2bjcbdg2lewoci5qvo4

MiningABs: mining associated biomarkers across multi-connected gene expression datasets

Chun-Pei Cheng, Christopher DeBoever, Kelly A Frazer, Yu-Cheng Liu, Vincent S Tseng
2014 BMC Bioinformatics  
Human disease often arises as a consequence of alterations in a set of associated genes rather than alterations to a set of unassociated individual genes. Most previous microarray-based meta-analyses identified disease-associated genes or biomarkers independent of genetic interactions. Therefore, in this study, we present the first meta-analysis method capable of taking gene combination effects into account to efficiently identify associated biomarkers (ABs) across different microarray
more » ... . Results: We propose a new meta-analysis approach called MiningABs to mine ABs across different array-based datasets. The similarity between paired probe sequences is quantified as a bridge to connect these datasets together. The ABs can be subsequently identified from an "improved" common logit model (c-LM) by combining several sibling-like LMs in a heuristic genetic algorithm selection process. Our approach is evaluated with two sets of gene expression datasets: i) 4 esophageal squamous cell carcinoma and ii) 3 hepatocellular carcinoma datasets. Based on an unbiased reciprocal test, we demonstrate that each gene in a group of ABs is required to maintain high cancer sample classification accuracy, and we observe that ABs are not limited to genes common to all platforms. Investigating the ABs using Gene Ontology (GO) enrichment, literature survey, and network analyses indicated that our ABs are not only strongly related to cancer development but also highly connected in a diverse network of biological interactions. Conclusions: The proposed meta-analysis method called MiningABs is able to efficiently identify ABs from different independently performed array-based datasets, and we show its validity in cancer biology via GO enrichment, literature survey and network analyses. We postulate that the ABs may facilitate novel target and drug discovery, leading to improved clinical treatment. Java source code, tutorial, example and related materials are available at "http://sourceforge.net/projects/miningabs/".
doi:10.1186/1471-2105-15-173 pmid:24909518 pmcid:PMC4068973 fatcat:dswkhsj6dvglrnoaf7d4wd32ly

Mining differential top-k co-expression patterns from time course comparative gene expression datasets

Yu-Cheng Liu, Chun-Pei Cheng, Vincent S Tseng
2013 BMC Bioinformatics  
Frequent pattern mining analysis applied on microarray dataset appears to be a promising strategy for identifying relationships between gene expression levels. Unfortunately, too many itemsets (co-expressed genes) are identified by this analysis method since it does not consider the importance of each gene within biological processes to a cellular response and does not take into account temporal properties under biological treatmentcontrol matched conditions in a microarray dataset. Results: We
more » ... propose a method termed TIIM (Top-k Impactful Itemsets Miner), which only requires specifying a userdefined number k to explore the top k itemsets with the most significantly differentially co-expressed genes between 2 conditions in a time course. To give genes different weights, a table with impact degrees for each gene was constructed based on the number of neighboring genes that are differently expressed in the dataset within gene regulatory networks. Finally, the resulting top-k impactful itemsets were manually evaluated using previous literature and analyzed by a Gene Ontology enrichment method. Conclusions: In this study, the proposed method was evaluated in 2 publicly available time course microarray datasets with 2 different experimental conditions. Both datasets identified potential itemsets with co-expressed genes evaluated from the literature and showed higher accuracies compared to the 2 corresponding control methods: i) performing TIIM without considering the gene expression differentiation between 2 different experimental conditions and impact degrees, and ii) performing TIIM with a constant impact degree for each gene. Our proposed method found that several new gene regulations involved in these itemsets were useful for biologists and provided further insights into the mechanisms underpinning biological processes. The Java source code and other related materials used in this study are available at "http://websystem.csie.ncku.edu.tw/ TIIM_Program.rar". Background Identification of relationships between gene regulatory events is one of the main methods through which the biological effects of stimuli or changes in the environment are revealed. Microarrays are a highly efficient way to simultaneously measure the expression of massive numbers of genes. In these respects, multiple microarrays could be further used to quantify the expression of each gene during time course experiments. However, analysis and proper presentation of biological insights into these large-scale datasets is a big challenge. Currently, frequent pattern-based mining analysis is widely used to identify groups of genes that are frequently co-expressed in most biological conditions in a microarray dataset. These methods include using the apriori algorithm [1], half-spaces [2], relational-based analysis [3], gene annotation integrated method [4], row enumerationbased method [5], column enumeration-based method [6], temporal-based method [7], rule induction [8], and FPtree algorithm [9]. A gene itemset {gene x↑, gene y↓, gene z↑} states that upregulation of gene x, downregulation of gene y and upregulation of gene z frequently occur at the
doi:10.1186/1471-2105-14-230 pmid:23870110 pmcid:PMC3751367 fatcat:b2v3x2t2gzh6dh3vyfs3t4wkhq

Topological Link Models of Multipartite Entanglement

Ning Bao, Newton Cheng, Sergio Hernández-Cuenca, Vincent Paul Su
2022 Quantum  
We introduce a novel model of multipartite entanglement based on topological links, generalizing the graph/hypergraph entropy cone program. We demonstrate that there exist link representations of entropy vectors which provably cannot be represented by graphs or hypergraphs. Furthermore, we show that the contraction map proof method generalizes to the topological setting, though now requiring oracular solutions to well-known but difficult problems in knot theory.
doi:10.22331/q-2022-06-20-741 fatcat:dllq2eju6nffznvh5ypw3yju5u

Respond to China's Rise and Engage Taiwan

Vincent Wei-cheng Wang
2009 Asia Policy  
" • Respond to China's Rise and Engage Taiwan Vincent Wei-cheng Wang B arack Obama's election as president of the United States is not only a watershed event in U.S. history but also a fresh start  ...  wei-cheng wang is the Chairman of the Department of Political Science at the University of Richmond.  ... 
doi:10.1353/asp.2009.0066 fatcat:x7ctdtj2pjgndcljmif2anzypi

Visitation policies and practices in US ICUs

Vincent Liu, Julia Read, Elizabeth Scruth, Eugene Cheng
2013 Critical Care  
Prior reports suggest that restrictive ICU visitation policies can negatively impact patients and their loved ones. However, visitation practices in US ICUs, and the hospital factors associated with them, are not well described. Methods: A telephone survey was made of ICUs, stratified by US region and hospital type (community, federal, or university), between 2008 and 2009. Hospital characteristics were self-reported and included the hospitals' bed number, critical care unit number, and
more » ... of ICU leadership. Hospital and ICU visitation restrictions were based on five criteria: visiting hours; visit duration; number of visitors; age of visitors; and membership in the patient's immediate family. Hospitals or ICUs without restrictions had open visitation policies; those with any restriction had restrictive policies. Results: The study surveyed 606 hospitals in the Northeast (17.0%), Midwest (26.2%), South (36.6%), and West (20.1%) regions; most were community hospitals (n = 401, 66.2%). The mean hospital size was 239 ± 217 beds; the mean percentage of ICU beds was 11.6% ± 13.4%. Hospitals often had restrictive hospital (n = 463, 76.4%) and ICU (n = 543, 89.6%) visitation policies. Many ICUs had ≥ 3 restrictions (n = 375; 61.9%), most commonly related to visiting hours and visitor number or age. Nearly all ICUs allowed visitation exceptions (n = 474; 94.8%). ICUs with open policies were more common in hospitals with < 150 beds. Among restrictive ICUs, the bed size, hospital type, number of critical care units, and ICU leadership were not associated with the number of restrictions. On average, hospitals in the Midwest had the least restrictive policies, while those in the Northeast had the most restrictive. Conclusion: In 2008 the overwhelming majority of US ICUs in this study had restrictive visitation policies. Wide variability in visitation policies suggests that further study into the impact of ICU visitations on care and outcomes remains necessary to standardize practice. Data presented as number (percentage) or mean ± standard deviation. Liu et al. Critical Care 2013, 17:R71 http://ccforum.com/content/17/2/R71 Liu et al. Critical Care 2013, 17:R71
doi:10.1186/cc12677 pmid:23591058 pmcid:PMC4056772 fatcat:3udfjjdenjgtxf3t4bdtj7xche

Prospects for U.S.-Taiwan Relations

Vincent Wei-cheng Wang
2016 Orbis: Journal of World Affairs  
For an analysis of this official silence, see Vincent Wei-cheng Wang, "The U.S.  ...  Wei-cheng Wang, "President Chen Shui-bian's Mainland China Policy: Normalizing or Electioneering the Cross-Strait Impasse?"  ... 
doi:10.1016/j.orbis.2016.08.004 fatcat:6mvlfahhpbhqpdypengsxo44xy

The quantum entropy cone of hypergraphs

Ning Bao, Newton Cheng, Sergio Hernández-Cuenca, Vincent P. Su
2020 SciPost Physics  
In this work, we generalize the graph-theoretic techniques used for the holographic entropy cone to study hypergraphs and their analogously-defined entropy cone. This allows us to develop a framework to efficiently compute entropies and prove inequalities satisfied by hypergraphs. In doing so, we discover a class of quantum entropy vectors which reach beyond those of holographic states and obey constraints intimately related to the ones obeyed by stabilizer states and linear ranks. We show
more » ... at least up to 4 parties, the hypergraph cone is identical to the stabilizer entropy cone, thus demonstrating that the hypergraph framework is broadly applicable to the study of entanglement entropy. We conjecture that this equality continues to hold for higher party numbers and report on partial progress on this direction. To physically motivate this conjectured equivalence, we also propose a plausible method inspired by tensor networks to construct a quantum state from a given hypergraph such that their entropy vectors match.
doi:10.21468/scipostphys.9.5.067 fatcat:x2ry2lxvxbetbi4ktypk43junu

Photoacoustic Silk Scaffolds for Neural stimulation and Regeneration [article]

Nan Zheng, Vincent Fitzpatrick, Ran Cheng, Linli Shi, David L. Kaplan, Chen Yang
2021 arXiv   pre-print
Neural interfaces using biocompatible scaffolds provide crucial properties for the functional repair of nerve injuries and neurodegenerative diseases, including cell adhesion, structural support, and mass transport. Neural stimulation has also been found to be effective in promoting neural regeneration. This work provides a new strategy to integrate photoacoustic (PA) neural stimulation into hydrogel scaffolds using a nanocomposite hydrogel approach. Specifically, polyethylene glycol
more » ... ionalized carbon nanotubes (CNT), highly efficient photoacoustic agents, are embedded into silk fibroin to form biocompatible and soft photoacoustic materials. We show that these photoacoustic functional scaffolds enable non-genetic activation of neurons with a spatial precision defined by the area of light illumination, promoting neuron regeneration. These CNT/silk scaffolds offered reliable and repeatable photoacoustic neural stimulation. 94% of photoacoustic stimulated neurons exhibit a fluorescence change larger than 10% in calcium imaging in the light illuminated area. The on-demand photoacoustic stimulation increased neurite outgrowth by 1.74-fold in a dorsal root ganglion model, when compared to the unstimulated group. We also confirmed that photoacoustic neural stimulation promoted neurite outgrowth by impacting the brain-derived neurotrophic factor (BDNF) pathway. As a multifunctional neural scaffold, CNT/silk scaffolds demonstrated non-genetic PA neural stimulation functions and promoted neurite outgrowth, providing a new method for non-pharmacological neural regeneration.
arXiv:2106.14362v1 fatcat:j6yf4tvj4vdy7jhyibn4wc525e

Mining Top-K Association Rules [chapter]

Philippe Fournier-Viger, Cheng-Wei Wu, Vincent S. Tseng
2012 Lecture Notes in Computer Science  
Mining association rules is a fundamental data mining task. However, depending on the choice of the parameters (the minimum confidence and minimum support), current algorithms can become very slow and generate an extremely large amount of results or generate too few results, omitting valuable information. This is a serious problem because in practice users have limited resources for analyzing the results and thus are often only interested in discovering a certain amount of results, and fine
more » ... ng the parameters is timeconsuming. To address this problem, we propose an algorithm to mine the top-k association rules, where k is the number of association rules to be found and is set by the user. The algorithm utilizes a new approach for generating association rules named rule expansions and includes several optimizations. Experimental results show that the algorithm has excellent performance and scalability, and that it is an advantageous alternative to classical association rule mining algorithms when the user want to control the number of rules generated.
doi:10.1007/978-3-642-30353-1_6 fatcat:uefkboqnc5edtcgdwdl3rmpy44

Grid Cyber-Security Strategy in an Attacker-Defender Model

Yu-Cheng Chen, Vincent John Mooney, Santiago Grijalva
2021 Cryptography  
The progression of cyber-attacks on the cyber-physical system is analyzed by the Probabilistic, Learning Attacker, and Dynamic Defender (PLADD) model. Although our research does apply to all cyber-physical systems, we focus on power grid infrastructure. The PLADD model evaluates the effectiveness of moving target defense (MTD) techniques. We consider the power grid attack scenarios in the AND configurations and OR configurations. In addition, we consider, for the first time ever, power grid
more » ... ck scenarios involving both AND configurations and OR configurations simultaneously. Cyber-security managers can use the strategy introduced in this manuscript to optimize their defense strategies. Specifically, our research provides insight into when to reset access controls (such as passwords, internet protocol addresses, and session keys), to minimize the probability of a successful attack. Our mathematical proof for the OR configuration of multiple PLADD games shows that it is best if all access controls are reset simultaneously. For the AND configuration, our mathematical proof shows that it is best (in terms of minimizing the attacker′s average probability of success) that the resets are equally spaced apart. We introduce a novel concept called hierarchical parallel PLADD system to cover additional attack scenarios that require combinations of AND and OR configurations.
doi:10.3390/cryptography5020012 fatcat:fxuicufexnht5hvntuxkbgo6ri

Topological Link Models of Multipartite Entanglement [article]

Ning Bao, Newton Cheng, Sergio Hernández-Cuenca, Vincent Paul Su
2022 arXiv   pre-print
We introduce a novel model of multipartite entanglement based on topological links, generalizing the graph/hypergraph entropy cone program. We demonstrate that there exist link representations of entropy vectors which provably cannot be represented by graphs or hypergraphs. Furthermore, we show that the contraction map proof method generalizes to the topological setting, though now requiring oracular solutions to well-known but difficult problems in knot theory.
arXiv:2109.01150v2 fatcat:tmw2hmq24ze67auywf35nfzayy

Detecting, estimating and correcting multipath biases affecting GNSS signals using a marginalized likelihood ratio-based method

Cheng Cheng, Jean-Yves Tourneret, Quan Pan, Vincent Calmettes
2016 Signal Processing  
OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. This is an author-deposited version published in : http://oatao.univ-toulouse.fr/ Eprints ID : 14692 To link to this article : Keywords: Global navigation satellite systems Multipath mitigation Marginalized likelihood ratio test Multiple model Urban positioning a b s t r a c t In urban canyons, non-line-of-sight (NLOS) multipath interferences affect
more » ... n estimation based on global navigation satellite systems (GNSS). This paper proposes to model the effects of NLOS multipath interferences as mean value jumps contaminating the GNSS pseudo-range measurements. The marginalized likelihood ratio test (MLRT) is then investigated to detect, identify and estimate the corresponding NLOS multipath biases. However, the MLRT test statistics is difficult to compute. In this work, we consider a Monte Carlo integration technique based on bias magnitude sampling. Jensen's inequality allows this Monte Carlo integration to be simplified. The multiple model algorithm is also used to update the prior information for each bias magnitude sample. Some strategies are designed for estimating and correcting the NLOS multipath biases. In order to demonstrate the performance of the MLRT, experiments allowing several localization methods to be compared are performed. Finally, results from a measurement campaign conducted in an urban canyon are presented in order to evaluate the performance of the proposed algorithm in a representative environment. (J.-Y. Tourneret), quanpan@nwpu.edu.cn (Q. Pan), vincent.calmettes@isae.fr (V. Calmettes). 1 EURASIP member.
doi:10.1016/j.sigpro.2015.06.021 fatcat:4xs2kiwnj5aqzjgbuya4voztoq

Discovering relational-based association rules with multiple minimum supports on microarray datasets

Yu-Cheng Liu, Chun-Pei Cheng, Vincent S. Tseng
2011 Computer applications in the biosciences : CABIOS  
Recently, various types of analysis methods were proposed to analyze gene expression data, such as clustering analysis (Cheng and Church, 2000; Jiang et al., 2004; Madeira and Oliveira, 2004; Pei et al  ... 
doi:10.1093/bioinformatics/btr526 pmid:21926125 fatcat:v4itrxxjrzbirnc65zd5ymsrlq
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