34 research outputs found
Leveraging noisy side information for disentangling of factors of variation in a supervised setting
Ce mémoire est composé de trois articles et présente les résultats de travaux de recherche effectués dans le but d'améliorer les techniques actuelles permettant d'utiliser des données associées à certaines tùches dans le but d'aider à l'entraßnement de réseaux de neurones sur une tùche différente.
Les deux premiers articles présentent de nouveaux ensembles de données créés pour permettre une meilleure évaluation de ce type de techniques d'apprentissage machine. Le premier article introduit une suite d'ensembles de données pour la tùche de reconnaissance automatique de chiffres écrits à la main. Ces ensembles de données ont été générés à partir d'un ensemble de données déjà existant, MNIST, auquel des nouveaux facteurs de variation ont été ajoutés. Le deuxiÚme article introduit un ensemble de données pour la tùche de reconnaissance automatique d'expressions faciales. Cet ensemble de données est composé d'images de visages qui ont été collectées automatiquement à partir du Web et ensuite étiquetées.
Le troisiÚme et dernier article présente deux nouvelles approches, dans le contexte de l'apprentissage multi-tùches, pour tirer avantage de données pour une tùche donnée afin d'améliorer les performances d'un modÚle sur une tùche différente. La premiÚre approche est une généralisation des neurones Maxout récemment proposées alors que la deuxiÚme consiste en l'application dans un contexte supervisé d'une technique permettant d'inciter des neurones à apprendre des fonctions orthogonales, à l'origine proposée pour utilisation dans un contexte semi-supervisé.The thesis is composed of three articles and presents the results of research done in order to improve the current methods for improving a neural network's performance on a given task by taking advantage of data from other tasks.
The two first articles present new datasets created to allow better evaluation of this type of machine learning methods. The first article introduces a dataset suite for the task of handwritten digit recognition. This dataset suite was created from the existing dataset MNIST to which new factors of variation have been added. The second article introduces a new dataset for the task of facial expression recognition. It is composed of images of faces that were automatically collected from the Web and then labelled.
The third and last article presents two new approaches to improving performance on a task of interest by leveraging labels from another task in the context of multi-task learning. The first approach is a generalization of the recently introduced Maxout Networks designed for multi-task learning. The second approach consists in the application in a fully-supervised setting of the previously introduced Contractive Discriminant Analysis penalty, originally used in the semi-supervised setting to make groups of neurons learn features orthogonal to each other
Challenges in Representation Learning: A report on three machine learning contests
The ICML 2013 Workshop on Challenges in Representation Learning focused on
three challenges: the black box learning challenge, the facial expression
recognition challenge, and the multimodal learning challenge. We describe the
datasets created for these challenges and summarize the results of the
competitions. We provide suggestions for organizers of future challenges and
some comments on what kind of knowledge can be gained from machine learning
competitions.Comment: 8 pages, 2 figure
Validation of the Body Concealment Scale for Scleroderma (BCSS): Replication in the Scleroderma Patient-centered Intervention Network (SPIN) Cohort
© 2016 Elsevier Ltd Body concealment is an important component of appearance distress for individuals with disfiguring conditions, including scleroderma. The objective was to replicate the validation study of the Body Concealment Scale for Scleroderma (BCSS) among 897 scleroderma patients. The factor structure of the BCSS was evaluated using confirmatory factor analysis and the Multiple-Indicator Multiple-Cause model examined differential item functioning of SWAP items for sex and age. Internal consistency reliability was assessed via Cronbach's alpha. Construct validity was assessed by comparing the BCSS with a measure of body image distress and measures of mental health and pain intensity. Results replicated the original validation study, where a bifactor model provided the best fit. The BCSS demonstrated strong internal consistency reliability and construct validity. Findings further support the BCSS as a valid measure of body concealment in scleroderma and provide new evidence that scores can be compared and combined across sexes and ages
COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study
Background:
The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms.
Methods:
International, prospective observational study of 60â109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms.
Results:
âTypicalâ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (â€â18 years: 69, 48, 23; 85%), older adults (â„â70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each Pâ<â0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country.
Interpretation:
This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men
LâĂTUDE DE TRAJECTOIRES DâIMPLANTATION DE BAROMĂTRE, UN OUTIL NUMĂRIQUE VISANT Ă ACTUALISER LâAPPROCHE DE PERSONNALISATION DES SERVICES SOCIAUX
La personnalisation des services sociaux propose une approche de plus en plus valorisĂ©e dans les pratiques. Elle vise Ă offrir plus de choix et de contrĂŽle aux personnes en misant sur leurs forces pour coproduire lâintervention. Pour accompagner le changement de culture quâexige ce type dâapproche, un outil dâintervention informatisĂ© et interactif a Ă©tĂ© dĂ©veloppĂ©, nommĂ© BaromĂštre. Comment une technologie numĂ©rique comme BaromĂštre peut-elle agir comme condition sociotechnique contribuant au changement de culture? Nous avons rĂ©alisĂ© une recherche qualitative utilisant une stratĂ©gie dâĂ©tude de cas multiples. Quatre milieux de pratique nous ont servi dâobservatoires : deux organismes communautaires en santĂ© mentale, un dĂ©partement de psychiatrie et un centre de formation pour adultes. Trois types de collecte de donnĂ©es ont Ă©tĂ© utilisĂ©s : des entretiens individuels semi-directifs auprĂšs des usagers, des entretiens dâexplicitation de la pratique auprĂšs dâintervenants pour produire des histoires dâutilisation, des entretiens de groupe auprĂšs dâusagers et dâintervenants. Nous avons analysĂ© les donnĂ©es au moyen dâun modĂšle des forces croisant quatre modes opĂ©ratoires dâexpĂ©rimentation : gĂ©nĂ©raliste, expansionniste, particulariste et dĂ©liquescent. Lâanalyse permet dâobserver une tendance Ă la dĂ©liquescence des expĂ©rimentations-pilotes. Or, la dĂ©liquescence nâest pas causĂ©e par la technologie en elle-mĂȘme, mais par les conditions contextuelles des expĂ©rimentations.The individualization of social services proposes an approach that is increasingly valued in practice. It aims to offer more choices and control to people by building on their strengths to co-produce intervention. To support the cultural change required by this type of approach, a digital and interactive intervention tool has been developed, called BaromĂštre. How can a digital technology like BaromĂštre act as a socio-technical condition contributing to culture change? We conducted qualitative research using a multiple case studies strategy. Observations were made in four practice settings: two community mental health organizations, a department of psychiatry and an adult education center. Three types of data collection were used: individual semi-structured interviews with service users, practice clarification interviews with practitioners to produce narratives in relation to its use, and group interviews with service users and practitioners. The data was analyzed using four operational modes of experimentation: generalist, expansionist, particularist and deliquescent. The analysis shows a tendency towards deliquescence in pilot experiments. However, the delinquescence is not caused by the technology itself, but by the contextual conditions of the experiments
La personnalisation des services de santĂ© mentale : une voie dâavenir
La personnalisation des services de santĂ© mentale est indissociable dâun processus qui vise Ă penser et Ă circonscrire les effets recherchĂ©s par les personnes comme des aspirations lĂ©gitimes, Ă©largissant ainsi leurs possibilitĂ©s de choix et de contrĂŽle. Dans un premier temps, nous dĂ©montrerons que cette visĂ©e de personnalisation ne peut ĂȘtre dĂ©tachĂ©e dâun contexte gĂ©nĂ©ral et de contextes spĂ©cifiques, quâils soient français, anglo-saxons, quĂ©bĂ©cois ou autres. Lâapproche narrative constitue Ă cet Ă©gard un apport essentiel favorisant la prise en compte des liens de codĂ©termination entre façons de savoir et formes de pouvoir. Par la suite, les politiques, pratiques et recherches au Royaume-Uni en regard de la personnalisation seront mises en Ă©vidence avec un accent particulier sur les approches et outils dâintervention dans le champ de la santĂ© mentale. Câest dans ce cadre que nous prĂ©senterons le « Projet BaromĂštre » dont lâune des retombĂ©es est la conceptualisation dâun outil dâintervention et dâĂ©valuation, interactif et accessible via le web, qui met en Ă©vidence les forces et les progrĂšs de la personne dans sa communautĂ©.Objectives: To demonstrate the pertinence of putting personalisation at the heart of mental health services.Methods: Review of littĂ©rature of personalisation research and intervention in the United Kingdom, the country where the personalisation is one of the key themes of the health and social services reform agenda.Results: Presentation of the key challenges in the personalisation agenda and also of web tool directly inspired by research and practices in the UK.Conclusion: We think that individuals want to be treated as citizens that want control and choice over their destiny
Effects of intraoperative hemodynamic management on postoperative acute kidney injury in liver transplantation: An observational cohort study.
BACKGROUND:Intraoperative restrictive fluid management strategies might improve postoperative outcomes in liver transplantation. Effects of vasopressors within any hemodynamic management strategy are unclear. METHODS:We conducted an observational cohort study on adult liver transplant recipients between July 2008 and December 2017. We measured the effect of vasopressors infused at admission in the intensive care unit (ICU) and total intraoperative fluid balance. Our primary outcome was 48-hour acute kidney injury (AKI) and our secondary outcomes were 7-day AKI, need for postoperative renal replacement therapy (RRT), time to extubation in the ICU, time to ICU discharge and survival up to 1 year. We fitted models adjusted for confounders using generalized estimating equations or survival models using robust standard errors. We reported results with 95% confidence intervals. RESULTS:We included 532 patients. Vasopressors use was not associated with 48-hour or 7-day AKI but modified the effects of fluid balance on RRT and mortality. A higher fluid balance was associated with a higher need for RRT (OR = 1.52 [1.15, 2.01], p<0.001 for interaction) and lower survival (HR = 1.71 [1.26, 2.34], p<0.01 for interaction) only among patients without vasopressors. In patients with vasopressors, higher doses of vasopressors were associated with a higher mortality (HR = 1.29 [1.13, 1.49] per 10 ÎŒg/min of norepinephrine). CONCLUSION:The presence of any vasopressor at the end of surgery was not associated with AKI or RRT. The use of vasopressors might modify the harmful association between fluid balance and other postoperative outcomes. The liberal use of vasopressors to implement a restrictive fluid management strategy deserves further investigation
Crystal-GFN: sampling crystals with desirable properties and constraints
International audienceAccelerating material discovery holds the potential to greatly help mitigate the climate crisis. Discovering new solid-state materials such as electrocatalysts, superionic conductors or photovoltaic materials can have a crucial impact, for instance, in improving the efficiency of renewable energy production and storage. In this paper, we introduce Crystal-GFN, a generative model of crystal structures that sequentially samples structural properties of crystalline materials, namely the space group, composition and lattice parameters. This domain-inspired approach enables the flexible incorporation of physical and structural constraints, as well as the use of any available predictive model of a desired physico-chemical property as an objective function. To design stable materials, one must target the candidates with the lowest formation energy, which is used as an objective to evaluate the capabilities of Crystal-GFN. The formation energy of a crystal structure is predicted here by a new proxy model trained on MatBench. The results demonstrate that Crystal-GFN is able to sample diverse crystals with low formation energy