10,092 research outputs found
Metadata Representations for Queryable ML Model Zoos
No full textMachine learning (ML) practitioners and organizations are building model zoos of pre-trained models, containing metadata describing properties of the ML models and datasets that are useful for reporting, auditing, reproducibility, and interpretability purposes. The metatada is currently not standardised; its expressivity is limited; and there is no interoperable way to store and query it. Consequently, model search, reuse, comparison, and composition are hindered. In this paper, we advocate for standardized ML model metadata representation and management, proposing a toolkit supported to help practitioners manage and query that metadata.Web Information SystemsHuman-Centred Artificial Intelligenc
A Manifesto of Nodalism
No full textThis paper proposes the notion of Nodalism as a means describing contemporary culture and of understanding my own creative practice in electronic music composition. It draws on theories and ideas from Kirby, Bauman, Bourriaud, Deleuze, Guatarri, and Gochenour, to demonstrate how networks of ideas or connectionist neural models of cognitive behaviour can be used to contextualize, understand and become a creative tool for the creation of contemporary electronic music
Optimizing ML Inference Queries Under Constraints
No full textThe proliferation of pre-trained ML models in public Web-based model zoos facilitates the engineering of ML pipelines to address complex inference queries over datasets and streams of unstructured content. Constructing optimal plan for a query is hard, especially when constraints (e.g. accuracy or execution time) must be taken into consideration, and the complexity of the inference query increases. To address this issue, we propose a method for optimizing ML inference queries that selects the most suitable ML models to use, as well as the order in which those models are executed. We formally define the constraint-based ML inference query optimization problem, formulate it as a Mixed Integer Programming (MIP) problem, and develop an optimizer that maximizes accuracy given constraints. This optimizer is capable of navigating a large search space to identify optimal query plans on various model zoos.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Web Information SystemsHuman-Centred Artificial Intelligenc
Memoquin, a novel multifunctional compound for Alzheimer’s disease: an up-date on preclinical studies.
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Regenerative treatment using a radioelectric asymmetric conveyor as a novel tool in antiaging medicine: an in vitro beta-galactosidase study
No full textSalvatore Rinaldi,1,2 Margherita Maioli,1,3,4 Sara Santaniello,3,4 Alessandro Castagna,1,2 Gianfranco Pigliaru,3,4 Sara Gualini,3,4 Matteo Lotti Margotti,5 Arturo Carta,6 Vania Fontani,1,2 Carlo Ventura1,4,71Department of Regenerative Medicine, Rinaldi Fontani Institute, Florence; 2Department of Neuro Psycho Physio Pathology and Neuro Psycho Physical Optimization, Rinaldi Fontani Institute, Florence; 3Department of Biomedical Sciences, University of Sassari, Sassari; 4Laboratory of Molecular Biology and Stem Cell Engineering, National Institute of Biostructures and Biosystems, Bologna; 5Department of Information Technology and Statistical Analysis, Rinaldi Fontani Institute, Florence; 6Ophthalmology Section, University of Parma, Parma; 7Cardiovascular Department, S Orsola Malpighi Hospital, University of Bologna, Bologna, ItalyBackground: Beta-galactosidase is the most widely used biomarker for highlighting the processes of cellular aging, including neurodegeneration. On this basis, we decided to test in vitro whether a set of rescuing/reparative events previously observed by us in subjects treated with radioelectric asymmetric conveyor (REAC) technology may also involve antagonism of a marker of aging-related degenerative processes, as assessed by a reduction in beta-galactosidase at the cellular level.Methods: Human adipose-derived stem cells were cultured at different passages, ranging from 5 to 20, with or without REAC exposure for 12 hours. The cells were then processed for biochemical beta-galactosidase staining and morphological microscopy analysis.Results: We observed a significant reduction in expression of senescence associated-beta-galactosidase, and a persistence of fibroblast-like morphology typical of human adipose-derived stem cells, even at late passages.Conclusion: Our results indicate the ability of REAC technology to counteract in vitro senescence of human adipose-derived stem cells, and prompt the hypothesis that such technology may be exploited to antagonize in vivo senescence of tissue-resident or transplanted stem cells playing an important role in clinical treatment of age-related processes.Keywords: aging, adipose-derived stem cells, neurodegenerative disease
Building a generalisable ML pipeline at ING
No full textAdvances in data science have caused an increase in the use of Artificial Intelligence (AI), specifically Machine Learning (ML), throughout various fields. Not only in research but in the industry as well, has ML been receiving increasing amounts of interest. Many companies rely on ML models to increase the efficiency of existing processes or offer new services and products. The industry, however, is facing several additional challenges compared to the academic context. One of those challenges is applying the Development Operations (DevOps) model to an ML application, also referred to as MLOps. This thesis sets out to find the specific challenges that practitioners encounter while operationalising ML models. To do so, we perform a single-case case study on an ML pipeline built by the Trade & Communication Surveillance team at the ING bank. This case study consists of conducting a set of interviews and performing a manual code inspection of the pipeline. The team faces challenges ranging from having insufficient time for operationalising each ML project individually to operating in the highlyregulated fintech context. Their pipeline is able to deploy a single ML model but it does not generalise well to other projects. We present the first version of an application that mitigates these challenges. The application is able to deploy ML models to the development environment at ING and can be operated by data scientists to reduce the effort of operationalising an ML model. Computer Science | Software Technolog
Memoquin: A new therapeutic poly-agent for Alzheimer's disease
No full textIn this study, we present a new molecule, Memoquin, designed to display a range of activities potentially beneficial at distinct levels of the AD neuropathology. In vitro, this compound is able not only to inhibit acetylcholinesterase (AChE) activity, but it is also able to block in vitro the Abeta aggregation induced by AChE and shows anti-oxidant activity. In vivo, Memoquin was able to rescue, at the behavioral level, cognitive deficits in mice in which amnesia was induced by scopolamine and in AD11 anti-NGF transgenic mice. From the neuropathological point of view, in this comprehensive model for sporadic AD-like neurodegeneration, the oral admistration of Memoquin causes an effective recovery from the observed cholinergic deficit, tau hyperphosphorylation, beta-amyloid deposition. These findings show that a multiple therapeutic approach can be realized through properly designed molecules
'Project smells' - Experiences in Analysing the Software Quality of ML Projects with mllint
No full textMachine Learning (ML) projects incur novel challenges in their development and productionisation over traditional software applications, though established principles and best practices in ensuring the project's software quality still apply. While using static analysis to catch code smells has been shown to improve software quality attributes, it is only a small piece of the software quality puzzle, especially in the case of ML projects given their additional challenges and lower degree of Software Engineering (SE) experience in the data scientists that develop them. We introduce the novel concept of project smells which consider deficits in project management as a more holistic perspective on software quality in ML projects. An open-source static analysis tool mllint was also implemented to help detect and mitigate these. Our research evaluates this novel concept of project smells in the industrial context of ING, a global bank and large software- and data-intensive organisation. We also investigate the perceived importance of these project smells for proof-of-concept versus production-ready ML projects, as well as the perceived obstructions and benefits to using static analysis tools such as mllint. Our findings indicate a need for context-aware static analysis tools, that fit the needs of the project at its current stage of development, while requiring minimal configuration effort from the user. Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Software EngineeringSoftware Technolog
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