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

Influence of diabetes mellitus on heart failure risk and outcome

Our aim is to summarize and discuss the recent literature linking diabetes mellitus with heart failure, and to address the issue of the optimal treatment for diabetic patients with heart failure. THE STUDIES LINKING DIABETES MELLITUS (DM) WITH HEART FAILURE (HF): The prevalence of diabetes mellitus in heart failure populations is close to 20% compared with 4 to 6% in control populations. Epidemiological studies have demonstrated an increased risk of heart failure in diabetics; moreover, in diabetic populations, poor glycemic control has been associated with an increased risk of heart failure. Various mechanisms may link diabetes mellitus to heart failure: firstly, associated comorbidities such as hypertension may play a role; secondly, diabetes accelerates the development of coronary atherosclerosis; thirdly, experimental and clinical studies support the existence of a specific diabetic cardiomyopathy related to microangiopathy, metabolic factors or myocardial fibrosis. Subgroup analyses of randomized trials demonstrate that diabetes is also an important prognostic factor in heart failure. In addition, it has been suggested that the deleterious impact of diabetes may be especially marked in patients with ischemic cardiomyopathy. TREATMENT OF HEART FAILURE IN DIABETIC PATIENTS: The knowledge of the diabetic status may help to define the optimal therapeutic strategy for heart failure patients. Cornerstone treatments such as ACE inhibitors or beta-blockers appear to be uniformly beneficial in diabetic and non diabetic populations. However, in ischemic cardiomyopathy, the choice of the revascularization technique may differ according to diabetic status. Finally, clinical studies are needed to determine whether improved metabolic control might favorably influence the outcome of diabetic heart failure patients

EmoNets: Multimodal deep learning approaches for emotion recognition in video

The task of the emotion recognition in the wild (EmotiW) Challenge is to assign one of seven emotions to short video clips extracted from Hollywood style movies. The videos depict acted-out emotions under realistic conditions with a large degree of variation in attributes such as pose and illumination, making it worthwhile to explore approaches which consider combinations of features from multiple modalities for label assignment. In this paper we present our approach to learning several specialist models using deep learning techniques, each focusing on one modality. Among these are a convolutional neural network, focusing on capturing visual information in detected faces, a deep belief net focusing on the representation of the audio stream, a K-Means based "bag-of-mouths" model, which extracts visual features around the mouth region and a relational autoencoder, which addresses spatio-temporal aspects of videos. We explore multiple methods for the combination of cues from these modalities into one common classifier. This achieves a considerably greater accuracy than predictions from our strongest single-modality classifier. Our method was the winning submission in the 2013 EmotiW challenge and achieved a test set accuracy of 47.67% on the 2014 dataset

An active dipole for cosmic ray radiodetection with CODALEMA

A paraître dans NIM AInternational audienceThe CODALEMA experiment detects the electromagnetic pulses radiated during the development of Extensive Air Showers (EAS). Since 2005, in addition to spiral log-periodic antennas, ultra broad bandwidth active dipoles have been designed to detect the full electric pulse shape of these signals. A few performances of these new detectors are presented

CODALEMA: a cosmic ray air shower radio detection experiment

International audienceThe CODALEMA experimental device currently detects and characterizes the radio contribution of cosmic ray air showers : arrival directions and electric field topologies of radio transient signals associated to cosmic rays are extracted from the antenna signals. The measured rate, about 1 event per day, corresponds to an energy threshold around 5.10$^{16}$eV. These results allow to determine the perspectives offered by the present experimental design for radiodetection of Ultra High Energy Cosmic Rays at a larger scale

Evidence for Radio Detection of Extensive Air Showers Induced by Ultra High Energy Cosmic Rays

Firm evidence for a radio emission counterpart of cosmic ray air showers is presented. By the use of an antenna array set up in coincidence with ground particle detectors, we find a collection of events for which both time and arrival direction coincidences between particle and radio signals are observed. The counting rate corresponds to shower energies $\gtrsim 5\times 10^{16}$ eV. These results open overwhelming perspectives to complete existing detection methods for the observation of ultra high-energy cosmic rays.Comment: 4 pages, 4 figure

Theano: new features and speed improvements.

Abstract 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

Expression and implication of clusterin in left ventricular remodeling after myocardial infarction

International audienceBACKGROUND: Left ventricular remodeling (LVR) after myocardial infarction is associated with an increased risk of heart failure and death. In spite of a modern therapeutic approach, LVR remains relatively frequent and difficult to predict in clinical practice. Our aim was to identify new biomarkers of LVR and understand their involvement in its development.METHODS AND RESULTS:Proteomic analysis of plasma from the REVE-2 study (Remodelage Ventriculaire)-a study dedicated to the analysis of LVR which included 246 patients after a first anterior myocardial infarction-identified increased plasma levels of CLU (clusterin) in patients with high LVR. We used a rat model of myocardial infarction to analyze CLU expression in the LV and found a significant increase that was correlated with LVR parameters. We found increased CLU expression and secretion in primary cultures of rat neonate cardiomyocytes hypertrophied by isoproterenol. Silencing of CLU in hypertrophied neonate cardiomyocytes induced a significant decrease in cell size, ANP (atrial natriuretic peptide), and BNP (B-type natriuretic peptide) expression, associated with a decreased ERK (extracellular signal-regulated kinase) 1/2 activity, suggesting a prohypertrophic role of CLU. We then confirmed a significant increase of both intracellular p-CLU (precursor form of CLU) and m-CLU (mature form of CLU) in failing human hearts. Finally, the circulating levels of CLU (secreted form) were increased in patients with chronic heart failure who died from cardiovascular cause during a 3-year follow-up (n=99) compared with survivors (n=99).CONCLUSIONS: Our results show for the first time that plasma CLU levels are associated with LVR post-myocardial infarction, have in part a cardiac origin, and are a predictor of early death in heart failure patients