Calcul en n-dimensions sur GPU

Le code source de la libraire développée accompagne ce dépôt dans l'état où il était à ce moment. Il est possible de trouver une version plus à jour sur github (http://github.com/abergeron).Le calcul scientifique sur processeurs graphiques (GPU) est en plein essor depuis un certain temps, en particulier dans le domaine de l'apprentissage machine. Cette thèse présente les efforts pour établir une structure de données de table au multidimensionnel de manière efficace sur GPU. Nous commençons par faire une revue de ce qui est actuellement similaire dans le domaine et des désavantages d'avoir une multitude d'approches. Nous nous intéresserons particulièrement aux calculs fait à partir du langage Python. Nous décrirons des techniques intéressantes telles que la réduction d'ordre et le calcul asynchrone automatique. Pour terminer nous présenterons l'utilisation du module développé dans le cadre de cette thèse.Scientific computing on GPU (graphical processing units) is on the rise, specifically in machine learning. This thesis presents the implementation of an efficient multidimensional array on the GPU. We will begin by a review of what currently implements similar functionality and the disadvantage of a fragmented approach. We will focus on packages that have a Python interface. We will explain techniques to optimize execution such as order reduction and automatic asynchronous computations. Finally, we will present the functionality of the module developed for this thesis

XMM observations of the narrow-line QSO PHL 1092: Detection of a high and variable soft component

We present results based on an XMM-Newton observation of the high luminosity narrow-line QSO PHL 1092 performed in 2003 January. The 0.3 - 10 keV spectrum is well described by a model which includes a power-law (Gamma ~ 2.1) and two blackbody components (kT ~ 130 eV and kT ~ 50 eV). The soft X-ray excess emission is featureless and contributes ~ 80% to the total X-ray emission in the 0.3 - 10 keV band. The most remarkable feature of the present observation is the detection of X-ray variability at very short time scale: the X-ray emission varied by 35% in about 5000 s. We find that this variability can be explained by assuming that only the overall normalization varied during the observation. There was no evidence for any short term spectral variability and the spectral shape was similar even during the ASCA observation carried out in 1997. Considering the high intrinsic luminosity (~ 2x10^45 erg/s) and the large inferred mass of the putative black hole (~ 1.6x10^8 M_sun), the observed time scale of variability indicates emission at close to Eddington luminosity arising from very close to the black hole. We suggest that PHL 1092 in particular (and narrow line Seyfert galaxies in general) is a fast rotating black hole emitting close to its Eddington luminosity and the X-ray emission corresponds to the high-soft state seen in Galactic black hole sources.Comment: 7 figures, 8 pages, emulateapj style, ApJ in pres

Theano: new features and speed improvements

Theano is a linear algebra compiler that optimizes a user's symbolically-specified mathematical computations to produce efficient low-level implementations. In this paper, we present new features and efficiency improvements to Theano, and benchmarks demonstrating Theano's performance relative to Torch7, a recently introduced machine learning library, and to RNNLM, a C++ library targeted at recurrent neural networks.Comment: Presented at the Deep Learning Workshop, NIPS 201

Deep Self-Taught Learning for Handwritten Character Recognition

Recent theoretical and empirical work in statistical machine learning has demonstrated the importance of learning algorithms for deep architectures, i.e., function classes obtained by composing multiple non-linear transformations. Self-taught learning (exploiting unlabeled examples or examples from other distributions) has already been applied to deep learners, but mostly to show the advantage of unlabeled examples. Here we explore the advantage brought by {\em out-of-distribution examples}. For this purpose we developed a powerful generator of stochastic variations and noise processes for character images, including not only affine transformations but also slant, local elastic deformations, changes in thickness, background images, grey level changes, contrast, occlusion, and various types of noise. The out-of-distribution examples are obtained from these highly distorted images or by including examples of object classes different from those in the target test set. We show that {\em deep learners benefit more from out-of-distribution examples than a corresponding shallow learner}, at least in the area of handwritten character recognition. In fact, we show that they beat previously published results and reach human-level performance on both handwritten digit classification and 62-class handwritten character recognition

Occupational Factors and Socioeconomic Differences in Breast Cancer Risk and Stage at Diagnosis in Swiss Working Women.

Socioeconomic differences in breast cancer (BC) incidence are driven by differences in lifestyle, healthcare use and occupational exposure. Women of high socioeconomic status (SES) have a higher risk of BC, which is diagnosed at an earlier stage, than in low SES women. As the respective effects of occupation and SES remain unclear, we examined the relationships between occupation-related variables and BC incidence and stage when considering SES. Female residents of western Switzerland aged 18-65 years in the 1990 or 2000 census, with known occupation, were linked with records of five cancer registries to identify all primary invasive BC diagnosed between 1990 and 2014 in this region. Standardized incidence ratios (SIRs) were computed by occupation using general female population incidence rates, with correction for multiple comparisons. Associations between occupation factors and BC incidence and stage at diagnosis were analysed by negative binomial and multinomial logistic regression models, respectively. The cohort included 381,873 women-years and 8818 malignant BC, with a mean follow-up of 14.7 years. Compared with reference, three occupational groups predominantly associated with a high socioprofessional status had SIRs > 1: legal professionals (SIR = 1.68, 95%CI: 1.27-2.23), social science workers (SIR = 1.29; 95%CI: 1.12-1.49) and some office workers (SIR = 1.14; 95%CI: 1.09-1.20). Conversely, building caretakers and cleaners had a reduced incidence of BC (SIR = 0.69, 95%CI: 0.59-0.81). Gradients in BC risk with skill and socioprofessional levels persisted when accounting for SES. A higher incidence was generally associated with a higher probability of an early-stage BC. Occupation and SES may both contribute to differences in risk and stage at diagnosis of BC

Estimating 10-year risk of lung and breast cancer by occupation in Switzerland.

INTRODUCTION Lung and breast cancer are important in the working-age population both in terms of incidence and costs. The study aims were to estimate the 10-year risk of lung and breast cancer by occupation and smoking status and to create easy to use age-, and sex-specific 10-year risk charts. METHODS New lung and breast cancer cases between 2010 and 2014 from all 5 cancer registries of Western Switzerland, matched with the Swiss National Cohort were used. The 10-year risks of lung and breast cancer by occupational category were estimated. For lung cancer, estimates were additionally stratified by smoking status using data on smoking prevalence from the 2007 Swiss Health Survey. RESULTS The risks of lung and breast cancer increased with age and were the highest for current smokers. Men in elementary professions had a higher 10-year risk of developing lung cancer compared to men in intermediate and managerial professions. Women in intermediate professions had a higher 10-year risk of developing lung cancer compared to elementary and managerial professions. However, women in managerial professions had the highest risk of developing breast cancer. DISCUSSION The 10-year risk of lung and breast cancer differs substantially between occupational categories. Smoking creates greater changes in 10-year risk than occupation for both sexes. The 10-year risk is interesting for both patients and professionals to inform choices related to cancer risk, such as screening and health behaviors. The risk charts can also be used as public health indicators and to inform policies to protect workers

Large-Scale Automatic Feature Selection for Biomarker Discovery in High-Dimensional OMICs Data

The identification of biomarker signatures in omics molecular profiling is usually performed to predict outcomes in a precision medicine context, such as patient disease susceptibility, diagnosis, prognosis, and treatment response. To identify these signatures, we have developed a biomarker discovery tool, called BioDiscML. From a collection of samples and their associated characteristics, i.e., the biomarkers (e.g., gene expression, protein levels, clinico-pathological data), BioDiscML exploits various feature selection procedures to produce signatures associated to machine learning models that will predict efficiently a specified outcome. To this purpose, BioDiscML uses a large variety of machine learning algorithms to select the best combination of biomarkers for predicting categorical or continuous outcomes from highly unbalanced datasets. The software has been implemented to automate all machine learning steps, including data pre-processing, feature selection, model selection, and performance evaluation. BioDiscML is delivered as a stand-alone program and is available for download at https://github.com/mickaelleclercq/BioDiscML

Photometric variability of the unique magnetic white dwarf GD356

GD356 is a magnetic white dwarf (B = 13MG) that uniquely displays weak resolved Zeeman triplets of Halpha and Hbeta in emission. As such, GD356 may be the only known white dwarf with some kind of chromosphere, although accretion from the interstellar medium or more exotic mechanisms cannot be ruled out. Here, we report the detection of low amplitude (+/-~0.2%) near-sinusoidal photometric (V-band) variability in GD356, with a period of 0.0803 days (~115 minutes). We interpret this as the rotation period of the star. We model the variability with a dark spot (by analogy with star spots) covering 10% of the stellar surface. It seems likely that this spot is also the site of the Zeeman emission, requiring the presence of a temperature inversion. We show that the spot is never totally visible or obscured, and that both polar and equatorial spots produce good fits to the data when viewed at high and low inclination respectively.Comment: 5 pages, 3 figures, accepted MNRAS Letters, corrected page setu

The Origins of a Rich Absorption Line Complex in a Quasar at Redshift 3.45

We discuss the nature and origin of a rich complex of narrow absorption lines in the quasar J102325.31+514251.0 at redshift 3.447. We measure nine C IV(\lambda1548,1551) absorption line systems with velocities from -1400 to -6200 km/s, and full widths at half minimum ranging from 16 to 350 km/s. We also detect other absorption lines in these systems, including H I, C III, N V, O VI, and Si IV. Lower ionisation lines are not present, indicating a generally high degree of ionisation in all nine systems. The total hydrogen column densities range from <=10^{17.2} to 10^{19.1}cm^{-2}. We examine several diagnostics to estimate more directly the location and origin of each absorber. Four of the systems can be attributed to a quasar-driven outflow based on line profiles that are smooth and broad compared to thermal line widths. Several systems also have other indicators of a quasar outflow origin, including partial covering. Altogether there is direct evidence for 6 of the 9 systems forming in a quasar outflow. Consistent with a near-quasar origin, eight of the systems have metallicity values or lower limits in the range Z >= 1-8 Z_{sun}. The lowest velocity system, which has an ambiguous location, also has the lowest metallicity, Z <= 0.3 Z_{sun}, and might form in a non-outflow environment farther from the quasar. Overall, however, this complex of narrow absorption lines can be identified with a highly structured, multi-component outflow from the quasar. The high metallicities are similar to those derived for other quasars at similar redshifts and luminosities, and are consistent with evolution scenarios wherein quasars appear after the main episodes of star formation and metal enrichment in the host galaxies.Comment: 16 pages, 12 figures, Accepted to MNRAS, July 201