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[Submitted on 2 Aug 2024] View a PDF of the paper titled FIVB ranking: Misstep in the right direction, by Salma Tenni and 2 other authors View PDF HTML (experimental) Abstract:This work uses a statistical framework to present and evaluate the ranking algorithm that has been used by Fédération Internationale de Volleyball (FIVB) since 2020. The salient feature of the FIVB ranking is the use of the probabilistic model, which explicitly calculates the probabilities of the games to come. This explicit modeling is new in the context of official ranking, and we study the optimality of its parameters as well…

arXiv:2408.01481v1 Announce Type: new Abstract: Assessing artistic creativity has long challenged researchers, with traditional methods proving time-consuming. Recent studies have applied machine learning to evaluate creativity in drawings, but not paintings. Our research addresses this gap by developing a CNN model to automatically assess the creativity of students' paintings. Using a dataset of 600 paintings by professionals and children, our model achieved 90% accuracy and faster evaluation times than human raters. This approach demonstrates the potential of machine learning in advancing artistic creativity assessment, offering a more efficient alternative to traditional methods. Source link lol

arXiv:2408.01748v1 Announce Type: new Abstract: What would happen if temperatures were subdued and result in a cool summer? One can easily imagine that air conditioner, ice cream or beer sales would be suppressed as a result of this. Less obvious is that agricultural shipments might be delayed, or that sound proofing material sales might decrease. The ability to extract such causal knowledge is important, but it is also important to distinguish between cause-effect pairs that are known and those that are likely to be unknown, or rare. Therefore, in this paper, we propose a method for extracting rare causal knowledge…