Dominating Set Model Aggregation for communication-efficient decentralized deep learning.

Decentralized deep learning algorithms leverage peer-to-peer communication of model parameters and/or gradients over communication graphs among the learning agents with access to their private data sets. The majority of the studies in this area focus on achieving high accuracy, with many at the expense of increased communication overhead among the agents. However, large peer-to-peer communication overhead often becomes a practical challenge, especially in harsh environments such as for an underwater sensor network.

On Consensus-Optimality Trade-offs in Collaborative Deep Learning.

In distributed machine learning, where agents collaboratively learn from diverse private data sets, there is a fundamental tension between and . In this paper, we build on recent algorithmic progresses in distributed deep learning to explore various consensus-optimality trade-offs over a fixed communication topology. First, we propose the -based distributed stochastic gradient descent (i-CDSGD) algorithm, which involves multiple consensus steps (where each agent communicates information with its neighbors) within each SGD iteration.

Modeling and multiobjective optimization of indoor airborne disease transmission risk and associated energy consumption for building HVAC systems.

The COVID-19 pandemic has renewed interest in assessing how the operation of HVAC systems influences the risk of airborne disease transmission in buildings. Various processes, such as ventilation and filtration, have been shown to reduce the probability of disease spread by removing or deactivating exhaled aerosols that potentially contain infectious material. However, such qualitative recommendations fail to specify of these or other disinfection techniques are needed to achieve acceptable risk levels in a particular space.

[Vaginal repair operation for anterior pelvic organ prolapse in elderly women].

Objective: To identify the safety and efficacy of individualized vaginal surgery for anterior pelvic organ prolapse (POP) in elderly women so as to provide a clinical basis for studies on improving life quality by treatment in elderly women.

Methods: The individuation group consisted of 90 patients with a diagnosis of anterior POP. All over 60 years old, they underwent individualized vaginal surgery.