A number of initiatives invite members the public to perform online classification tasks such as identifying objects in images. These are crucial numerous large-scale Citizen Science projects different disciplines, with volunteers using their knowledge and support tools to, for example, identify species wildlife or classify galaxies by shapes. However, complex tasks, this case study on bumblebe...

Abstract In this paper, we focus on unsupervised representation learning for clustering of images. Recent advances in deep and are based the idea that different views an input image (generated through data augmentation techniques) must be close space (exemplar consistency), and/or similar images have cluster assignments (population consistency). We define additional notion consistency, consensu...

In this paper, we study the problem of consensus building in multi-robot systems with information feedback. We show how information feedback can be incorporated into the consensus building process so as to improve the robustness and situational awareness of the whole team. We detail the strategies of introducing feedback to the consensus building process through information flow, time-varying w...

This paper presents the abstraction of lazy consensus and argues for its use as an effective component for building distributed agreement protocols in practical asynchronous systems where processes and links can crash and recover. Lazy consensus looks like consensus, is equivalent to consensus, but is not consensus. The specification of lazy consensus has an ondemand and a re-entrant flavors th...