Variational Bayes model averaging for graphon functions and motif frequencies inference in W-graph models

W-graph refers to a general class of random graph models that can be seen as a random graph limit. It is characterized by both its graphon function and its motif frequencies. In this paper, relying on an existing variational Bayes algorithm for the stochastic block models along with the corresponding weights for model averaging, we derive an estimate of the graphon function as an average of stochastic block models with increasing number of blocks. In the same framework, we derive the variational posterior frequency of any motif. A simulation study and an illustration on a social network complete our work

Computing the Exponential of Large Block-Triangular Block-Toeplitz Matrices Encountered in Fluid Queues

The Erlangian approximation of Markovian fluid queues leads to the problem of computing the matrix exponential of a subgenerator having a block-triangular, block-Toeplitz structure. To this end, we propose some algorithms which exploit the Toeplitz structure and the properties of generators. Such algorithms allow to compute the exponential of very large matrices, which would otherwise be untreatable with standard methods. We also prove interesting decay properties of the exponential of a generator having a block-triangular, block-Toeplitz structure

A Spectral Algorithm with Additive Clustering for the Recovery of Overlapping Communities in Networks

This paper presents a novel spectral algorithm with additive clustering designed to identify overlapping communities in networks. The algorithm is based on geometric properties of the spectrum of the expected adjacency matrix in a random graph model that we call stochastic blockmodel with overlap (SBMO). An adaptive version of the algorithm, that does not require the knowledge of the number of hidden communities, is proved to be consistent under the SBMO when the degrees in the graph are (slightly more than) logarithmic. The algorithm is shown to perform well on simulated data and on real-world graphs with known overlapping communities.Comment: Journal of Theoretical Computer Science (TCS), Elsevier, A Para\^itr

c-Jun reprograms Schwann cells of injured nerves to generate a repair cell essential for regeneration.

The radical response of peripheral nerves to injury (Wallerian degeneration) is the cornerstone of nerve repair. We show that activation of the transcription factor c-Jun in Schwann cells is a global regulator of Wallerian degeneration. c-Jun governs major aspects of the injury response, determines the expression of trophic factors, adhesion molecules, the formation of regeneration tracks and myelin clearance and controls the distinctive regenerative potential of peripheral nerves. A key function of c-Jun is the activation of a repair program in Schwann cells and the creation of a cell specialized to support regeneration. We show that absence of c-Jun results in the formation of a dysfunctional repair cell, striking failure of functional recovery, and neuronal death. We conclude that a single glial transcription factor is essential for restoration of damaged nerves, acting to control the transdifferentiation of myelin and Remak Schwann cells to dedicated repair cells in damaged tissue

MAGMA : inference and prediction using multi-task Gaussian processes with common mean

A novel multi-task Gaussian process (GP) framework is proposed, by using a common mean process for sharing information across tasks. In particular, we investigate the problem of time series forecasting, with the objective to improve multiple-step-ahead predictions. The common mean process is defined as a GP for which the hyper-posterior distribution is tractable. Therefore an EM algorithm is derived for handling both hyper-parameters optimisation and hyper-posterior computation. Unlike previous approaches in the literature, the model fully accounts for uncertainty and can handle irregular grids of observations while maintaining explicit formulations, by modelling the mean process in a unified GP framework. Predictive analytical equations are provided, integrating information shared across tasks through a relevant prior mean. This approach greatly improves the predictive performances, even far from observations, and may reduce significantly the computational complexity compared to traditional multi-task GP models. Our overall algorithm is called MAGMA (standing for Multi tAsk GPs with common MeAn). The quality of the mean process estimation, predictive performances, and comparisons to alternatives are assessed in various simulated scenarios and on real datasets

Paris COP 21: Power that Speaks the Truth?

© 2016 Informa UK Limited, trading as Taylor & Francis Group In this paper, I set out some of the key aspects of the Paris COP 21 Climate Change Agreement. The Paris Agreement was initially reported as a major success. However, this was in so far as many thought any kind of agreement at all was unlikely, and because the Agreement includes Article 2: an aspiration to maintain average global temperature increases to significantly less than 2°C. I then ask the question: if the Paris Agreement is a success of sorts, has anything fundamental changed in order to translate the conditional success of achieving an agreement into an actual success that will realise the goals of the Agreement? I address this in terms of early assessment of trends and the Nationally Determined Contributions, how responsibility is positioned in the Agreement, and the political economy context, which has called forth the need for an agreement

Modelling the time-varying cell capacity in LTE networks

In wireless orthogonal frequency-division multiple access (OFDMA) based networks like Long Term Evolution (LTE) or Worldwide Interoperability for Microwave Access (WiMAX) a technique called adaptive modulation and coding (AMC) is applied. With AMC, different modulation and coding schemes (MCSs) are used to serve different users in order to maximise the throughput and range. The used MCS depends on the quality of the radio link between the base station and the user. Data is sent towards users with a good radio link with a high MCS in order to utilise the radio resources more efficiently while a low MCS is used for users with a bad radio link. Using AMC however has an impact on the cell capacity as the quality of a radio link varies when users move around; this can even lead to situations where the cell capacity drops to a point where there are too little radio resources to serve all users. AMC and the resulting varying cell capacity notably has an influence on admission control (AC). AC is the algorithm that decides whether new sessions are allowed to a cell or not and bases its decisions on, amongst others, the cell capacity. The analytical model that is developed in this paper models a cell with varying capacity caused by user mobility using a continuous -time Markov chain (CTMC). The cell is divided into multiple zones, each corresponding to the area in which data is sent towards users using a certain MCS and transitions of users between these zones are considered. The accuracy of the analytical model is verified by comparing the results obtained with it to results obtained from simulations that model the user mobility more realistically. This comparison shows that the analytical model models the varying cell capacity very accurately; only under extreme conditions differences between the results are noticed. The developed analytical and simulation models are then used to investigate the effects of a varying cell capacity on AC. Also, an optimisation algorithm that adapts the parameter of the AC algorithm which determines the amount of resources that are reserved in order to mitigate the effects of the varying cell capacity is studied using the models. Updating the parameter of the AC algorithm is done by reacting to certain triggers that indicate good or bad performance and adapt the parameters of the AC algorithm accordingly. Results show that using this optimisation algorithm improves the quality of service (QoS) that is experienced by the users.This work was partially supported by the Spanish Government through project TIN2010-21378-C02-02 and contract BES-2007-15030.Sas, B.; Bernal Mor, E.; Spaey, K.; Pla, V.; Blondia, C.; Martínez Bauset, J. (2014). Modelling the time-varying cell capacity in LTE networks. 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