首页|New Machine Learning Findings from Lund University Discussed (Agreements ‘in the Wild’: Standards and Alignment In Machine Learning Benchmark Dataset Constructi on)
New Machine Learning Findings from Lund University Discussed (Agreements ‘in the Wild’: Standards and Alignment In Machine Learning Benchmark Dataset Constructi on)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting out of Lund, Sweden, by NewsR x editors, the research stated, “This article presents an ethnographic case stud y of a corporate-academic group constructing a benchmark dataset of daily activi ties for a variety of machine learning and computer vision tasks. Using a socio- technical perspective, the article conceptualizes the dataset as a knowledge obj ect that is stabilized by both practical standards (for daily activities, datafi cation, annotation and benchmarks) and alignment work - that is, efforts includi ng forging agreements to make these standards effective in practice.”Financial supporters for this research include European Research Council (ERC), STS environment in Sweden. Our news journalists obtained a quote from the research from Lund University, “B y attending to alignment work, the article highlights the informal, communicativ e and supportive efforts that underlie the success of standards and the smoothin g of tensions between actors and factors. Emphasizing these efforts constitutes a contribution in several ways. This article’s ethnographic mode of analysis cha llenges and supplements quantitative metrics on datasets. It advances the field of dataset analysis by offering a detailed empirical examination of the developm ent of a new benchmark dataset as a collective accomplishment. By showing the im portance of alignment efforts and their close ties to standards and their limita tions, it adds to our understanding of how machine learning datasets are built.”
LundSwedenEuropeCyborgsEmerging TechnologiesMachine LearningLund University
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