418 research outputs found
A new non-convex framework to improve asymptotical knowledge on generic stochastic gradient descent
Stochastic gradient optimization methods are broadly used to minimize
non-convex smooth objective functions, for instance when training deep neural
networks. However, theoretical guarantees on the asymptotic behaviour of these
methods remain scarce. Especially, ensuring almost-sure convergence of the
iterates to a stationary point is quite challenging. In this work, we introduce
a new Kurdyka-Lojasiewicz theoretical framework to analyze asymptotic behavior
of stochastic gradient descent (SGD) schemes when minimizing non-convex smooth
objectives. In particular, our framework provides new almost-sure convergence
results, on iterates generated by any SGD method satisfying mild conditional
descent conditions. We illustrate the proposed framework by means of several
toy simulation examples. We illustrate the role of the considered theoretical
assumptions, and investigate how SGD iterates are impacted whether these
assumptions are either fully or partially satisfied
Stochastic Majorize-Minimize Subspace Algorithm with Application to Binary Classification
International audienceIn a learning context, data distribution are usually unknown. Observation models are also sometimes complex. In an inverse problem setup, these facts often lead to the minimization of a loss function with uncertain analytic expression. Consequently, its gradient cannot be evaluated in an exact manner. These issues have has promoted the development of so-called stochastic optimization methods, which are able to cope with stochastic errors in the gradient term. A natural strategy is to start from a deterministic optimization approach as a baseline, and to incorporate a stabilization procedure (e.g., decreasing stepsize, averaging) that yields improved robustness to stochastic errors. In the context of large-scale, differentiable optimization, an important class of methods relies on the principle of majorization-minimization (MM). MM algorithms are becoming increasingly popular in signal/image processing and machine learning. MM approaches are fast, stable, require limited manual settings, and are often preferred by practitioners in application domains such as medical imaging and telecommunications. The present work introduces novel theoretical convergence guarantees for MM algorithms when approximate gradient terms are employed, generalizing some recent work to a wider class of functions and algorithms. We illustrate our theoretical results with a binary classification problem
Numériser et mettre en ligne des archives personnelles dans un établissement public (aspects juridiques)
La Fiche explore les aspects juridiques liés à la numérisation et la mise en ligne des archives personnelles pour un établissement public. Cela implique les précautions à prendre dans le cadre d’une opération de numérisation, ainsi que les conditions de réutilisation des documents numériques
Use of morbidity and mortality conferences to analyze causes of death at sea: a useful tool in the process of training in maritime medicine
Background. Morbidity and mortality conferences (MandMC) are collective reviews of records of
patients, whose evolution was marked by an undesirable event: death or the occurrence of
complications. The MandMC aim to improve the quality of care. This article intends to present three
cases analyzed in MandMC in the French Telemedical Assistance Service (TMAS).
Material and methods. Three cases were selected according to the occurrence of a death at
sea or according to particular cases of pathology on board. The case presentation was done in
plenary session in our French TMAS, describing the facts, analyzing the defective processes,
and suggesting possible improvements for each case.
Results. Description of 3 cases: Gastroenteritis in Papua New Guinea with septic shock; traumatic
brain injury on a training boat with organizational and evacuation problems, and fever in
the Gulf of Guinea with negative thick blood smear test.
Conclusions. The MandMC tend to develop in all medical fields and are of particular interest in
maritime medicine. The achievement of MandMC in our TMAS highlighted some difficulties in our
daily work: diagnosis difficulty in tele-consultation and organizational or operational difficulties
related to maritime medicine. However, we hope that the proposals for improvement will be
applied to improve the quality of maritime medical care.
(Int Marit Health 2011; 62, 2: 104–109
The efficacy of a task model approach to ADL rehabilitation in stroke apraxia and action disorganisation syndrome:A randomised controlled trial
BACKGROUND: Apraxia and action disorganization syndrome (AADS) after stroke can disrupt activities of daily living (ADL). Occupational therapy has been effective in improving ADL performance, however, inclusion of multiple tasks means it is unclear which therapy elements contribute to improvement. We evaluated the efficacy of a task model approach to ADL rehabilitation, comparing training in making a cup of tea with a stepping training control condition. METHODS: Of the 29 stroke survivors with AADS who participated in this cross-over randomized controlled feasibility trial, 25 were included in analysis [44% females; mean(SD) age = 71.1(7.8) years; years post-stroke = 4.6(3.3)]. Participants attended five 1-hour weekly tea making training sessions in which progress was monitored and feedback given using a computer-based system which implemented a Markov Decision Process (MDP) task model. In a control condition, participants received five 1-hour weekly stepping sessions. RESULTS: Compared to stepping training, tea making training reduced errors across 4 different tea types. The time taken to make a cup of tea was reduced so the improvement in accuracy was not due to a speed-accuracy trade-off. No improvement linked to tea making training was evident in a complex tea preparation task (making two different cups of tea simultaneously), indicating a lack of generalisation in the training. CONCLUSIONS: The clearly specified but flexible training protocol, together with information on the distribution of errors, provide pointers for further refinement of task model approaches to ADL rehabilitation. It is recommended that the approach be tested under errorless learning conditions with more impaired patients in future research. TRIAL REGISTRATION: Retrospectively registered at ClinicalTrials.gov on 5(th) August 2019 [NCT04044911] https://clinicaltrials.gov/ct2/show/NCT04044911?term=Cogwatch&rank=
VITRUV - Imaging close environments of stars and galaxies with the VLTI at milli-arcsec resolution
The VITRUV project has the objective to deliver milli-arcsecond
spectro-images of the environment of compact sources like young stars, active
galaxies and evolved stars to the community. This instrument of the VLTI second
generation based on the integrated optics technology is able to combine from 4
to 8 beams from the VLT telescopes. Working primarily in the near infrared, it
will provide intermediate to high spectral resolutions and eventually
polarization analysis. This paper summarizes the result from the concept study
led within the Joint Research Activity advanced instruments of the OPTICON
program.Comment: In "The Power of Optical/IR Interferometry: Recent Scientific Results
and 2nd Generation VLTI Instrumentation", Allemagne (2005) in pres
A CD31-derived peptide prevents angiotensin II-induced atherosclerosis progression and aneurysm formation.
International audienceAIMS: The loss of the inhibitory receptor CD31 on peripheral T lymphocytes is associated with the incidence of atherosclerotic complications such as abdominal aortic aneurysms (AAA) in patients and plaque thrombosis in mice. However, we have recently discovered that a small fragment of extracellular CD31 remains expressed on the surface of the apparently 'CD31-negative' T-cells and that it is possible to restore the CD31-mediated T-cell inhibition in vivo by using a synthetic CD31-derived peptide. Here, we wanted to evaluate the therapeutic potential of the peptide in an experimental model of accelerated atherosclerosis and AAA formation. METHODS AND RESULTS: The effect of the murine CD31-derived peptide (aa 551-574, 1.5 mg/kg/day, sc) was evaluated on the extent of atherosclerotic plaques and the incidence of AAA in 28-week-old apolipoprotein E knockout mice (male, n ≥ 8/group) submitted to chronic angiotensin II infusion. The therapeutic mechanisms of the peptide were assessed by evaluating its effect on immune cell functions in vivo and in vitro. The prevalence of angiotensin II-induced AAA correlated with the loss of extracellular CD31 on T-cells. CD31 peptide treatment reduced both aneurysm formation and plaque size (P < 0.05 vs. control). Protection was associated with reduced perivascular leucocyte infiltration and T-cell activation in vivo. Functional in vitro studies showed that the peptide is able to suppress both T-cell and macrophage activation. CONCLUSION: CD31 peptides could represent a new class of drugs intended to prevent the inflammatory cell processes, such as those underlying progression of atherosclerosis and development of AAA
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