Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression

We consider the optimization of a quadratic objective function whose gradients are only accessible through a stochastic oracle that returns the gradient at any given point plus a zero-mean finite variance random error. We present the first algorithm that achieves jointly the optimal prediction error rates for least-squares regression, both in terms of forgetting of initial conditions in O(1/n 2), and in terms of dependence on the noise and dimension d of the problem, as O(d/n). Our new algorithm is based on averaged accelerated regularized gradient descent, and may also be analyzed through finer assumptions on initial conditions and the Hessian matrix, leading to dimension-free quantities that may still be small while the " optimal " terms above are large. In order to characterize the tightness of these new bounds, we consider an application to non-parametric regression and use the known lower bounds on the statistical performance (without computational limits), which happen to match our bounds obtained from a single pass on the data and thus show optimality of our algorithm in a wide variety of particular trade-offs between bias and variance

An observation of circular RNAs in bacterial RNA-seq data

Circular RNAs (circRNAs) are a class of RNA with an important role in micro RNA (miRNA) regulation recently discovered in Human and various other eukaryotes as well as in archaea. Here, we have analyzed RNA-seq data obtained from {\it Enterococcus faecalis} and {\it Escherichia coli} in a way similar to previous studies performed on eukaryotes. We report observations of circRNAs in RNA-seq data that are reproducible across multiple experiments performed with different protocols or growth conditions

On Convergence-Diagnostic based Step Sizes for Stochastic Gradient Descent

Constant step-size Stochastic Gradient Descent exhibits two phases: a transient phase during which iterates make fast progress towards the optimum, followed by a stationary phase during which iterates oscillate around the optimal point. In this paper, we show that efficiently detecting this transition and appropriately decreasing the step size can lead to fast convergence rates. We analyse the classical statistical test proposed by Pflug (1983), based on the inner product between consecutive stochastic gradients. Even in the simple case where the objective function is quadratic we show that this test cannot lead to an adequate convergence diagnostic. We then propose a novel and simple statistical procedure that accurately detects stationarity and we provide experimental results showing state-of-the-art performance on synthetic and real-world datasets

On The Joint Modeling of The Behavior of Social Insects and Their Interaction With Environment by Taking Into Account Physical Phenomena Like Anisotropic Diffusion

International audienceThis work takes place in the framework of GEODIFF project (funded by CNRS) and deals with the general issue of the social behavior modeling of pest insects with a particular focus on Bark Beetles. Bark Beetles are responsible for pine trees devastation in North America since 2005. In order to stem the problem and to apply an adapted strategy, one should be able to predict the evolution of the population of Bark Beetles. More precisely, a model taking into account a given population of insects (a colony) interacting with its environment, the forest ecosystem, would be very helpful. In a previous work, we aimed to model diffusive phenomenons across the environment using a simple reactive Multi-agent System. Bark beetle use pheromones as a support for recruitment of other bark beetles in the neighborhood in order to achieve a mass attack over a tree. They are first attracted by the ethanol or other phytopheromones emitted by a sick, stressed or dead tree and reinforce the presence of other individuals amongst the targeted tree. Both ethanol and semiochemicals are transported through the forest thanks to the wind, thermic effects and this advection phenomenon is modulated by the topology of the environment, tree and other obstacles distribution. In other words, the environment is involved in the process of a bark beetle attack. The first modeling we used to tackle our objective was not spatially explicit as long as free space propagation only was taken into account (isotropic phenomenon) with no constraint imposed by the environment such as wind. This article is intended to take into account such physical phenomenons and push the modeling one step further by providing predictions driven by measures provided by a Geographical Information System

Epidemiology of equine infectious anemia in France and in Europe from 1994 to 2011

Equine Infectious Anaemia (EIA) is a viral disease affecting horses, mules, and donkeys. The virus, present worldwide, is a member of the Retroviridae family, genus Lentivirus, such as the Human Immunodeficiency Virus (HIV). It causes a persistent infection, often associated with recurrent clinical episodes characterized by viremia, fever, and anaemia. Asymptomatic infected animals serve as a reservoir for the virus and are contagious. EIA is endemic in Romania, whereas only sporadic cases have been notified in others European countries. To improve understanding and prevention of the viral and disease spread within the equine population, epidemiological surveys as well as molecular characterisation of strains isolated in Europe are required.L'Anémie Infectieuse des Equidés (AIE) est une maladie virale qui affecte les chevaux, les mulets et les ânes. Le virus responsable, présent dans le monde entier, de la maladie appartient à la famille des Retroviridae, genre lentivirus comme le Virus de l'Immunodéficience Humaine (VIH). Il provoque une infection persistante, souvent associée à des épisodes cliniques récurrents caractérisés par une viré-mie, de la fièvre et de l'anémie. Les animaux infectés asymptomatiques représentent le réservoir du virus et sont contagieux. La Roumanie et l'Italie sont les deux pays européens les plus touchés par la maladie seuls des cas sporadiques sont déclarés dans le reste de l'Europe. Afin de mieux comprendre et de mieux prévenir la dissémination du virus et de la maladie au sein de la population équine des enquêtes épidémiologiques et des études de caractérisation moléculaire des souches isolées en Europe sont nécessaires

On The Joint Modeling of The Behavior of Social Insects and Their Interaction With Environment by Taking Into Account Physical Phenomena Like Anisotropic Diffusion

This work takes place in the framework of GEODIFF project (funded by CNRS) and deals with the general issue of the social behavior modeling of pest insects with a particular focus on Bark Beetles. Bark Beetles are responsible for pine trees devastation in North America since 2005. In order to stem the problem and to apply an adapted strategy, one should be able to predict the evolution of the population of Bark Beetles. More precisely, a model taking into account a given population of insects (a colony) interacting with its environment, the forest ecosystem, would be very helpful. In a previous work, we aimed to model diffusive phenomenons across the environment using a simple reactive Multi-agent System. Bark beetle use pheromones as a support for recruitment of other bark beetles in the neighborhood in order to achieve a mass attack over a tree. They are first attracted by the ethanol or other phytopheromones emitted by a sick, stressed or dead tree and reinforce the presence of other individuals amongst the targeted tree. Both ethanol and semiochemicals are transported through the forest thanks to the wind, thermic effects and this advection phenomenon is modulated by the topology of the environment, tree and other obstacles distribution. In other words, the environment is involved in the process of a bark beetle attack. The first modeling we used to tackle our objective was not spatially explicit as long as free space propagation only was taken into account (isotropic phenomenon) with no constraint imposed by the environment such as wind. This article is intended to take into account such physical phenomenons and push the modeling one step further by providing predictions driven by measures provided by a Geographical Information System

Experimental Study of Collective Pedestrian Dynamics

We report on two series of experiments, conducted in the frame of two different collaborations designed to study how pedestrians adapt their trajectories and velocities in groups or crowds. Strong emphasis is put on the motivations for the chosen protocols and the experimental implementation. The first series deals with pattern formation, interactions between pedestrians, and decision-making in pedestrian groups at low to medium densities. In particular, we show how pedestrians adapt their headways in single-file motion depending on the (prescribed) leader’s velocity. The second series of experiments focuses on static crowds at higher densities, a situation that can be critical in real life and in which the pedestrians’ choices of motion are strongly constrained sterically. More precisely, we study the crowd’s response to its crossing by a pedestrian or a cylindrical obstacle of 74cm in diameter. In the latter case, for a moderately dense crowd, we observe displacements that quickly decay with the minimal distance to the obstacle, over a lengthscale of the order of the meter

Synthesis of branched-phosphodiester and mannosecentered fucosylated glycoclusters and their binding studies with Burkholderia ambifaria lectin (BambL)

Universite Montpellier 2, Region Rhoˆne-Alpes Cluster Chimie. A.A.International audienceFive fucosylated glycoclusters exhibiting 4, 6 or 8 residues were synthesised with two different spatial environments based on mannose-centered and branched-phosphodiester scaffolds. Their synthesis was performed in solution using phosphoramidite chemistry to generate phosphodiester linkages, combined with Cu(I)-catalyzed azide-alkyne cycloaddition (CuAAC). The multivalent ligands were evaluated for their ability to bind to Burkholderia ambifaria Lectin (BambL). Binding evaluation was performed through inhibition of hemagglutination (HIA), surface plasmon resonance (SPR) and isothermal titration microcalorimetry (ITC). All fucosylated glycoclusters exhibited a higher affinity to BambL than methyl α-L-fucoside. A dissociation constant of 43 nM was observed for the fucocluster exhibiting four residues with the branched-phosphodiester spatial environment corresponding to a 22-fold increase in comparison with methyl α-L-fucoside. These multivalent fucoclusters represent the first example of ligands of high affinity to BambL

BMI-related microstructural changes in the tibial subchondral trabecular bone of patients with knee osteoarthritis

Overweight is a risk factor for osteoarthritis on the knees. Subchondral trabecular bone (SCTB) densification has been shown to be associated with cartilage degeneration. This study analyzed the microarchitectural changes in the SCTB of tibial plateaus to validate the hypothesis that the degree of remodeling is correlated with a patient's body weight. Twenty-one tibial plateaus were collected during total knee arthroplasty from 21 patients (15 women and 6 men). These patients had a mean age of 70.4 years (49-81), mean weight of 74.7 kg (57-93) and mean body mass index (BMI) of 28.4 kg/m2 (21.3-40.8). One cylindrical plug was harvested in the center of each tibial plateau (medial and lateral). Micro-CT parameters (7.4 μm resolution) were determined to describe the SCTB structure. On the medial plateau, there were significant correlations between BMI and bone volume fraction BV/TV (r = 0.595, p = 0.004), structure model index SMI (r = -0.704 p = 0.0002), trabecular space Tb.Sp (r = 0.600, p = 0.04) and trabecular number Tb.N (r = 0.549, p = 0.01). SCTB densification during osteoarthritis is associated with a reduction in its elastic modulus, which could increase cartilage stress, and accelerate cartilage loss. SCTB densification has been shown to precede cartilage degeneration. The correlation of SCTB microarchitecture and body weight may explain why knee osteoarthritis is more common in overweight or obese patients