Semantic Segmentation of Human Model Using Heat Kernel and Geodesic Distance

A novel approach of 3D human model segmentation is proposed, which is based on heat kernel signature and geodesic distance. Through calculating the heat kernel signature of the point clouds of human body model, the local maxima of thermal energy distribution of the model is found, and the set of feature points of the model is obtained. Heat kernel signature has affine invariability which can be used to extract the correct feature points of the human model in different postures. We adopt the method of geodesic distance to realize the hierarchical segmentation of human model after obtaining the semantic feature points of human model. The experimental results show that the method can overcome the defect of geodesic distance feature extraction. The human body models with different postures can be obtained with the model segmentation results of human semantic characteristics

Stochastic Cahn-Hilliard Equations and Their Sharp Interface Limits

Yang H. Stochastic Cahn-Hilliard Equations and Their Sharp Interface Limits. Bielefeld: Universität Bielefeld; 2019

Sharp Interface Limit of Stochastic Cahn-Hilliard Equation with Singular Noise

We study the sharp interface limit of the two dimensional stochastic Cahn-Hilliard equation driven by two types of singular noise: a space-time white noise and a space-time singular divergence-type noise. We show that with appropriate scaling of the noise the solutions of the stochastic problems converge to the solutions of the determinisitic Mullins-Sekerka/Hele-Shaw problem

Federated Linear Contextual Bandits with User-level Differential Privacy

This paper studies federated linear contextual bandits under the notion of user-level differential privacy (DP). We first introduce a unified federated bandits framework that can accommodate various definitions of DP in the sequential decision-making setting. We then formally introduce user-level central DP (CDP) and local DP (LDP) in the federated bandits framework, and investigate the fundamental trade-offs between the learning regrets and the corresponding DP guarantees in a federated linear contextual bandits model. For CDP, we propose a federated algorithm termed as \robin and show that it is near-optimal in terms of the number of clients $M$ and the privacy budget $\varepsilon$ by deriving nearly-matching upper and lower regret bounds when user-level DP is satisfied. For LDP, we obtain several lower bounds, indicating that learning under user-level $(\varepsilon,\delta)$-LDP must suffer a regret blow-up factor at least {$\min\{1/\varepsilon,M\}$ or $\min\{1/\sqrt{\varepsilon},\sqrt{M}\}$} under different conditions.Comment: Accepted by ICML 202

Crowdsourcing contests to facilitate community engagement in HIV cure research: a qualitative evaluation of facilitators and barriers of participation.

BACKGROUND: As HIV cure research advances, there is an increasing need for community engagement in health research, especially in low- and middle-income countries with ongoing clinical trials. Crowdsourcing contests provide an innovative bottom-up way to solicit community feedback on clinical trials in order to enhance community engagement. The objective of this study was to identify facilitators and barriers to participating in crowdsourcing contests about HIV cure research in a city with ongoing HIV cure clinical trials. METHODS: We conducted in-depth interviews to evaluate facilitators and barriers to participating in crowdsourcing contests in Guangzhou, China. Contests included the following activities: organizing a call for entries, promoting the call, evaluating entries, celebrating exceptional entries, and sharing entries. We interviewed 31 individuals, including nine HIV cure clinical trial participants, 17 contest participants, and five contest organizers. Our sample included men who have sex with men (20), people living with HIV (14), and people who inject drugs (5). We audio-recorded, transcribed, and thematically analyzed the data using inductive and deductive coding techniques. RESULTS: Facilitators of crowdsourcing contest participation included responsiveness to lived experiences, strong community interest in HIV research, and community trust in medical professionals and related groups. Contests had more participants if they responded to the lived experiences, challenges, and opportunities of living with HIV in China. Strong community interest in HIV research helped to drive the formulation and execution of HIV cure contests, building support and momentum for these activities. Finally, participant trust in medical professionals and related groups (community-based organizations and contest organizers) further strengthened the ties between community members and researchers. Barriers to participating in crowdsourcing contests included persistent HIV stigma and myths about HIV. Stigma associated with discussing HIV made promotion difficult in certain contexts (e.g., city squares and schools). Myths and misperceptions about HIV science confused participants. CONCLUSIONS: Our data identified facilitators and barriers of participation in HIV cure crowdsourcing contests in China. Our findings could complement existing HIV community engagement strategies and help to design HIV contests for community engagement in other settings, particularly in low- and middle-income countries