Improving Pareto Front Learning via Multi-Sample Hypernetworks

Pareto Front Learning (PFL) was recently introduced as an effective approach to obtain a mapping function from a given trade-off vector to a solution on the Pareto front, which solves the multi-objective optimization (MOO) problem. Due to the inherent trade-off between conflicting objectives, PFL offers a flexible approach in many scenarios in which the decision makers can not specify the preference of one Pareto solution over another, and must switch between them depending on the situation. However, existing PFL methods ignore the relationship between the solutions during the optimization process, which hinders the quality of the obtained front. To overcome this issue, we propose a novel PFL framework namely PHN-HVI, which employs a hypernetwork to generate multiple solutions from a set of diverse trade-off preferences and enhance the quality of the Pareto front by maximizing the Hypervolume indicator defined by these solutions. The experimental results on several MOO machine learning tasks show that the proposed framework significantly outperforms the baselines in producing the trade-off Pareto front.Comment: Accepted to AAAI-2

A Framework for Controllable Pareto Front Learning with Completed Scalarization Functions and its Applications

Pareto Front Learning (PFL) was recently introduced as an efficient method for approximating the entire Pareto front, the set of all optimal solutions to a Multi-Objective Optimization (MOO) problem. In the previous work, the mapping between a preference vector and a Pareto optimal solution is still ambiguous, rendering its results. This study demonstrates the convergence and completion aspects of solving MOO with pseudoconvex scalarization functions and combines them into Hypernetwork in order to offer a comprehensive framework for PFL, called Controllable Pareto Front Learning. Extensive experiments demonstrate that our approach is highly accurate and significantly less computationally expensive than prior methods in term of inference time.Comment: Under Review at Neural Networks Journa

System for Performing Single Query Searches of Heterogeneous and Dispersed Databases

The present invention is a distributed computer system of heterogeneous databases joined in an information grid and configured with an Application Programming Interface hardware which includes a search engine component for performing user-structured queries on multiple heterogeneous databases in real time. This invention reduces overhead associated with the impedance mismatch that commonly occurs in heterogeneous database queries

Cathelicidin suppresses lipid accumulation and hepatic steatosis by inhibition of the CD36 receptor.

Background and objectivesObesity is a global epidemic which increases the risk of the metabolic syndrome. Cathelicidin (LL-37 and mCRAMP) is an antimicrobial peptide with an unknown role in obesity. We hypothesize that cathelicidin expression correlates with obesity and modulates fat mass and hepatic steatosis.Materials and methodsMale C57BL/6 J mice were fed a high-fat diet. Streptozotocin was injected into mice to induce diabetes. Experimental groups were injected with cathelicidin and CD36 overexpressing lentiviruses. Human mesenteric fat adipocytes, mouse 3T3-L1 differentiated adipocytes and human HepG2 hepatocytes were used in the in vitro experiments. Cathelicidin levels in non-diabetic, prediabetic and type II diabetic patients were measured by enzyme-linked immunosorbent assay.ResultsLentiviral cathelicidin overexpression reduced hepatic steatosis and decreased the fat mass of high-fat diet-treated diabetic mice. Cathelicidin overexpression reduced mesenteric fat and hepatic fatty acid translocase (CD36) expression that was reversed by lentiviral CD36 overexpression. Exposure of adipocytes and hepatocytes to cathelicidin significantly inhibited CD36 expression and reduced lipid accumulation. Serum cathelicidin protein levels were significantly increased in non-diabetic and prediabetic patients with obesity, compared with non-diabetic patients with normal body mass index (BMI) values. Prediabetic patients had lower serum cathelicidin protein levels than non-diabetic subjects.ConclusionsCathelicidin inhibits the CD36 fat receptor and lipid accumulation in adipocytes and hepatocytes, leading to a reduction of fat mass and hepatic steatosis in vivo. Circulating cathelicidin levels are associated with increased BMI. Our results demonstrate that cathelicidin modulates the development of obesity

Class based Influence Functions for Error Detection

Influence functions (IFs) are a powerful tool for detecting anomalous examples in large scale datasets. However, they are unstable when applied to deep networks. In this paper, we provide an explanation for the instability of IFs and develop a solution to this problem. We show that IFs are unreliable when the two data points belong to two different classes. Our solution leverages class information to improve the stability of IFs. Extensive experiments show that our modification significantly improves the performance and stability of IFs while incurring no additional computational cost.Comment: Thang Nguyen-Duc, Hoang Thanh-Tung, and Quan Hung Tran are co-first authors of this paper. 12 pages, 12 figures. Accepted to ACL 202

Genetic interaction between two VNTRs in the MAOA gene is associated with the nicotine dependence

Nicotine dependence is an addiction to tobacco products and a global public health concern that in part would be influenced by our genetics. Smokers are reported to have reduced MAOA activity, but the results from genetic associations with this gene have been inconclusive. Two functionally relevant variable number tandem repeat (VNTR) domains, termed uVNTR and dVNTR, in the MAOA gene are well characterized transcriptional regulatory elements. In the present study, we analyzed uVNTR and dVNTR polymorphisms in the MAOA gene in the Vietnamese male population of smokers and non-smokers in order to assess the association of MAOA with the nicotine dependence measured by the Fagerström Test for Nicotine Dependence (FTND). Individual analysis of VNTRs separately identified uVNTR to be associated with the F6 question of the FTND indicating the stronger addiction to nicotine. No associations were found between the dVNTR and smoking behavior. The combination of dVNTR and uVNTR, that predicts low expression of MAOA (10–3 haplotypes), was significantly associated with the higher nicotine dependence (FTND score), longer smoking duration, and more persistent smoking behavior (fewer quit attempts). In conclusion, our study confirms that low MAOA expression is genetically predictive to the higher nicotine dependence

A Systematic and Critical Review on the Research Landscape of Finance in Vietnam from 2008 to 2020

This paper endeavors to understand the research landscape of finance research in Vietnam during the period 2008 to 2020 and predict the key defining future research directions. Using the comprehensive database of Vietnam’s international publications in social sciences and humanities, we extract a dataset of 314 papers on finance topics in Vietnam from 2008 to 2020. Then, we apply a systematic approach to analyze four important themes: Structural issues, Banking system, Firm issues, and Financial psychology and behavior. Overall, there have been three noticeable trends within finance research in Vietnam: (1) assessment of financial policies or financial regulation, (2) deciphering the correlates of firms’ financial performances, and (3) opportunities and challenges in adopting innovations and ideas from foreign financial market systems. Our analysis identifies several fertile areas for future research, including financial market analysis in the post-COVID-19 eras, fintech, and green finance

Analytical study of the sth-order perturbative corrections to the solution to a one-dimensional harmonic oscillator perturbed by a spatially power-law potential Vper(x) = λxα

In this work, we present a rigorous mathematical scheme for the derivation of the sth-order perturbative corrections to the solution to a one-dimensional harmonic oscillator perturbed by the potential V-per(x) = lambda x(alpha), where alpha is a positive integer, using the non-degenerate time-independent perturbation theory. To do so, we derive a generalized formula for the integral I = integral(+infinity)(-infinity)x(alpha)exp(-x(2))H-n(x)H-m(x)d(x), where H-n(x) denotes the Hermite polynomial of degree n, using the generating function of orthogonal polynomials. Finally, the analytical results with alpha = 3 and alpha = 4 are discussed in detail and compared with the numerical calculations obtained by the Lagrange-mesh method

Mapping for engagement: setting up a community based participatory research project to reach underserved communities at risk for Hepatitis C in Ho Chi Minh City, Vietnam

Background: Approximately 1. 07 million people in Vietnam are infected with hepatitis C virus (HCV). To address this epidemic, the South East Asian Research Collaborative in Hepatitis (SEARCH) launched a 600-patient cohort study and two clinical trials, both investigating shortened treatment strategies for chronic HCV infection with direct-acting antiviral drugs. We conducted ethnographic research with a subset of trial participants and found that the majority were aware of HCV infection and its implications and were motivated to seek treatment. However, people who inject drugs (PWID), and other groups at risk for HCV were under-represented, although injecting drug use is associated with high rates of HCV. Material and Methods: We designed a community-based participatory research (CBPR) study to engage in dialogues surrounding HCV and other community-prioritized health issues with underserved groups at risk for HCV in Ho Chi Minh City. The project consists of three phases: situation analysis, CBPR implementation, and dissemination. In this paper, we describe the results of the first phase (i.e., the situation analysis) in which we conducted desk research and organized stakeholder mapping meetings with representatives from local non-government and community-based organizations where we used participatory research methods to identify and analyze key stakeholders working with underserved populations. Results: Twenty six institutions or groups working with the key underserved populations were identified. Insights about the challenges and dynamics of underserved communities were also gathered. Two working groups made up of representatives from the NGO and CBO level were formed. Discussion: Using the information provided by local key stakeholders to shape the project has helped us to build solid relationships, give the groups a sense of ownership from the early stages, and made the project more context specific. These steps are not only important preliminary steps for participatory studies but also for other research that takes place within the communities