12,281 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
Get PDFThis 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
Enhanced understanding of pathophysiology and phenotype in congenital afibrinogenemia using multiple global assays of coagulation
No full textBuilding 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
Development of five workshops to train department of medicine fellowship coordinators to redesign curriculum and teach buy-in tactics to comply with the next accreditation system education reform
Get PDF"O my luve's like a red, red, rose': does Burns's melody really matter?
No full textAn exploration of Burns's original choice of tune 'Major Graham's Strathspey' for his most famous love song. The essay provides a detailed publication history of the song and compares the melodies various editors have chosen over the past 200 years
Vitamin D and innate immunity in pneumonia and COPD
No full textA resurgence of interest in vitamin D research has led to the discovery that it plays a role in an unexpectedly large number of biological processes, and that reduced levels of this hormone are implicated in a range of diseases. In fact, it is estimated that vitamin D is involved in the regulation of 3% of the human genome. Two genes containing the target sequence indicative of vitamin D regulation are those encoding LL-37 and hBD-2. These antimicrobial peptides are integral components of the innate immune system and act as natural antibiotics to help combat infection.
The respiratory epithelium exposes a large surface area to environmental pathogens, making the innate immune response extremely important in its defence. Microbial infection of the respiratory tract is the cause of pneumonia, and is implicated in cases of COPD exacerbation. This study aimed to determine whether a relationship existed between vitamin D, LL-37 and hBD-2 in 185 patients admitted to Waikato hospital with either condition. It was hypothesised that low vitamin D would correlate with reduced peptide levels, and that this would be associated with increased infection severity and higher mortality rates.
Peptide concentrations in patient plasma were measured by indirect ELISA and compared to 25D levels. Statistical analysis revealed no significant associations between vitamin D status, peptide levels and severity, but did show increased mortality in individuals with severe vitamin D deficiency or low LL-37.
Based on the significance of LL-37 as a predictor of mortality (particularly in COPD), development of a plasma screening method using MALDI-TOF mass spectrometry was attempted, as a potential means of identifying patients most at risk. The success of this method was limited however, as the low abundance and small size of the mature peptide caused detection problems.
A protocol for assessing the vitamin D binding protein (DBP) genotype was developed, as it influences baseline 25D levels and response to supplementation. The association between low vitamin D and mortality suggests that supplementation could improve survival rates and, as the supplement dose required for effectiveness is genotype-dependent, this method could allow determination of the appropriate amount to administer to at-risk individuals
'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
Audiomobiles, Sculptures and Conundrums
No full textRoberto Gerhard was a pioneer of electronic music in England creating a number of substantial concert, theatre and radio works from as early as 1954. Gerhard’s electronic music is one of the richest repositories for understanding the development of the composer’s late compositional technique. Apart from the Symphony no.3, ‘Collages’, none of Gerhard’s electronic music is published. This paper will discuss aspects of Gerhard’s electronic music, focusing on Audiomobiles (1958-59) and Sculptures (1963)
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