Extracting extrusion cylinders from raw 3D geometry has been extensively researched in computer vision, while the processing of 3D data through neural networks has remained a bottleneck.

Thumbnails of dendrites are randomly colored.

We first validate ouralgorithm with manually decided loading strategiesinspired by variousexpertpriors,named PartialFed-Fix. Thenwedevelop PartialFed-Adaptive, which automatically selects personalized loading strategy for each client.

In this paper, we focus on computing an NE that optimizes a given objective function.

Several works haveshown this vulnerability via adversarial attacks, butexisting approaches onimproving therobustness ofDRL under this setting have limited success and lack for theoretical principles. We show that naively applying existing techniques on improving robustness for classification tasks,likeadversarialtraining,areineffectiveformanyRLtasks.

Topological data analysis (TDA) delivers invaluable and complementary information on the intrinsic properties of data inaccessible to conventional methods.

However, how to evaluate model performance in this challenging task is still unsolved.