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Register a new userThe EuroSys 2020 Online Conference: Experience and lessons learned
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Kostas Magoutis
Publication date
2020
fields
Informatics Engineering
and research's language is
English
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The 15th European Conference on Computer Systems (EuroSys20) was organized as a virtual (online) conference on April 27-30, 2020. The main EuroSys20 track took place April 28-30, 2020, preceded by five workshops (EdgeSys20, EuroDW20, EuroSec20, PaPoC20, SPMA20) on April 27, 2020. The decision to hold a virtual (online) conference was taken in early April 2020, after consultations with the EuroSys community and internal discussions about potential options, eventually allowing about three weeks for the organization. This paper describes the choices we made to organize EuroSys20 as a virtual (online) conference, the challenges we addressed, and the lessons learned.
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The virtual meeting was a success. Several people told us that this was the best virtual meeting they had seen so far, which, a year into the pandemic and without a commercial provider in the back, is a great success. The biggest point of criticism was the timing: We had programming from UTC 17:00-22:00 (evening and night in central Europe, afternoon on the US East Coast, during the day in South America and on the US West coast, but in the middle of the night for Asia and Australia). There is no good solution, but at least some variation in session time might go a long way to make it easier for all to attend at least some sessions. Feedback also indicates that the schedule was too compressed. Poster sessions and social contacts with the tool Gathertown worked out really well for all that used it. Our way of combining several services (Zoom for plenary and break-out rooms, Zenodo for uploading and viewing posters and proceedings, Google forms for registration and abstract submission, gathertown) allowed for a very low-cost meeting with little overhead (total cost: 600 $ for gathertown, zoom was provided through an institutional subscription, just 4 people on the LOC).
We review the EfficientQA competition from NeurIPS 2020. The competition focused on open-domain question answering (QA), where systems take natural language questions as input and return natural language answers. The aim of the competition was to build systems that can predict correct answers while also satisfying strict on-disk memory budgets. These memory budgets were designed to encourage contestants to explore the trade-off between storing large, redundant, retrieval corpora or the parameters of large learned models. In this report, we describe the motivation and organization of the competition, review the best submissions, and analyze system predictions to inform a discussion of evaluation for open-domain QA.
The emergence of the world-wide COVID-19 pandemic has forced academic conferences to be held entirely in a virtual manner. While prior studies have advocated the merits of virtual conferences in terms of energy and cost savings, organizers are increasingly facing the prospect of planning and executing them systematically, in order to deliver a rich conference-attending-experience for all participants. Starting from March 2020, tens of conferences have been held virtually. Past conferences have revealed numerous challenges, from budget planning, to selecting the supporting virtual platforms. Among these, two special challenges were identified: 1) how to deliver talks to geo-distributed attendees and 2) how to stimulate social interactions among attendees. These are the two important goals of an academic conference. In this paper, we advocate a mirror program approach for academic conferences. More specifically, the conference program is executed in multiple parallel (mirrored) programs, so that each mirror program can fit a different time zone. This can effectively address the first challenge.
Image captioning has recently demonstrated impressive progress largely owing to the introduction of neural network algorithms trained on curated dataset like MS-COCO. Often work in this field is motivated by the promise of deployment of captioning systems in practical applications. However, the scarcity of data and contexts in many competition datasets renders the utility of systems trained on these datasets limited as an assistive technology in real-world settings, such as helping visually impaired people navigate and accomplish everyday tasks. This gap motivated the introduction of the novel VizWiz dataset, which consists of images taken by the visually impaired and captions that have useful, task-oriented information. In an attempt to help the machine learning computer vision field realize its promise of producing technologies that have positive social impact, the curators of the VizWiz dataset host several competitions, including one for image captioning. This work details the theory and engineering from our winning submission to the 2020 captioning competition. Our work provides a step towards improved assistive image captioning systems.
Electrical energy consumption data accessibility for low voltage end users is one of the pillars of smart grids. In some countries, despite the presence of smart meters, a fragmentary data availability and/or the lack of standardization hinders the creation of post-metering value-added services and confines such innovative solutions to the prototypal and experimental level. We take inspiration from the technology adopted in Italy, where the national regulatory authority actively supported the definition of a solution agreed upon by all the involved stakeholders. In this context, smart meters are enabled to convey data to low voltage end users through a power line communication channel (CHAIN 2) in near real-time. The aim of this paper is twofold. On the one hand, it describes the proof of concept that the channel underwent and its subsequent validation (with performances nearing 99% success rate). On the other hand, it defines a classification framework (I2MA) for post-metering value-added services, in order to categorize each use case based on both level of service and expected benefits, and understand its maturity level. As an example, we apply the methodology to the 16 use cases defined in Italy. The lessons learned from the regulatory, technological, and functional approach of the Italian experience bring us to the provision of recommendations for researchers and industry experts. In particular, we argue that a well-functioning post-metering value-added services market can flourish when: i) distribution system operators certify the measurements coming from smart meters; ii) national regulatory authorities support the technological innovation needed for setting up this market; and iii) service providers create customer-oriented solutions based on smart meters data.
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