Dirichlet belief networks for topic structure learning

Recently, considerable research effort has been devoted to developing deep architectures for topic models to learn topic structures. Although several deep models have been proposed to learn better topic proportions of documents, how to leverage the benefits of deep structures for learning word distributions of topics has not yet been rigorously studied. Here we propose a new multi-layer generative process on word distributions of topics, where each layer consists of a set of topics and each topic is drawn from a mixture of the topics of the layer above. As the topics in all layers can be directly interpreted by words, the proposed model is able to discover interpretable topic hierarchies. As a self-contained module, our model can be flexibly adapted to different kinds of topic models to improve their modelling accuracy and interpretability. Extensive experiments on text corpora demonstrate the advantages of the proposed model.Comment: accepted in NIPS 201

Proximal Multitask Learning over Networks with Sparsity-inducing Coregularization

In this work, we consider multitask learning problems where clusters of nodes are interested in estimating their own parameter vector. Cooperation among clusters is beneficial when the optimal models of adjacent clusters have a good number of similar entries. We propose a fully distributed algorithm for solving this problem. The approach relies on minimizing a global mean-square error criterion regularized by non-differentiable terms to promote cooperation among neighboring clusters. A general diffusion forward-backward splitting strategy is introduced. Then, it is specialized to the case of sparsity promoting regularizers. A closed-form expression for the proximal operator of a weighted sum of $\ell_1$-norms is derived to achieve higher efficiency. We also provide conditions on the step-sizes that ensure convergence of the algorithm in the mean and mean-square error sense. Simulations are conducted to illustrate the effectiveness of the strategy

Generating Aspect-oriented Multi-document Summarization with Event-Aspect Model

In this paper, we propose a novel approach to automatic generation of aspect-oriented summaries from multiple documents. We first develop an event-aspect LDA model to cluster sentences into aspects. We then use extended LexRank algorithm to rank the sentences in each cluster. We use Integer Linear Programming for sentence selection. Key features of our method include automatic grouping of semantically related sentences and sentence ranking based on extension of random walk model. Also, we implement a new sentence compression algorithm which use dependency tree instead of parser tree. We compare our method with four baseline methods. Quantitative evaluation based on Rouge metric demonstrates the effectiveness and advantages of our method.

Angle-resolved photoemission study and first principles calculation of the electronic structure of GaTe

The electronic band structure of GaTe has been calculated by numerical atomic orbitals density-functional theory, in the local density approximation. In addition, the valence-band dispersion along various directions of the GaTe Brillouin zone has been determined experimentally by angle-resolved photoelectron spectroscopy. Along these directions, the calculated valence-band structure is in good concordance with the valence-band dispersion obtained by these measurements. It has been established that GaTe is a direct-gap semiconductor with the band gap located at the Z point, that is, at Brillouin zone border in the direction perpendicular to the layers. The valence-band maximum shows a marked \textit{p}-like behavior, with a pronounced anion contribution. The conduction band minimum arises from states with a comparable \textit{s}- \textit{p}-cation and \textit{p}-anion orbital contribution. Spin-orbit interaction appears to specially alter dispersion and binding energy of states of the topmost valence bands lying at $\Gamma$. By spin-orbit, it is favored hybridization of the topmost \textit{p}$_z$-valence band with deeper and flatter \textit{p$_x$}-\textit{p$_y$} bands and the valence-band minimum at $\Gamma$ is raised towards the Fermi level since it appears to be determined by the shifted up \textit{p$_x$}-\textit{p$_y$} bands.Comment: 7 text pages, 6 eps figures, submitted to PR

The chiral effective pion-nucleon Lagrangian of order p^4

We construct the minimal effective chiral pion-nucleon SU(2) Lagrangian at fourth order in the chiral expansion. The Lagrangian contains 118 in principle measurable terms. We develop both the relativistic as well as the heavy baryon formulation of the effective field theory. For the latter, we also work out explicitly all 1/m corrections at fourth order. We display all relevant relations needed to find the linearly independent terms.Comment: 30 pp, LaTeX2e, coefficients of three third order 1/m^2 corrections proportional to F_{\mu\nu}^+ corrected in eq.(3.8) and table

Endogenous Growth Models: Jones Vs Romer the Path to a Fully-Fledged Dynamic Analysis

The last two decades were marked by a high increase in economic growth research, namely related to three important issues as stated in Klenow et al. [1997]: world growth, country growth and dispersion in income levels. The Charles Jones’ [2002] technique to solve endogenous growth models relies on the two-step approach, which is in fact a clever way to study the dynamic behaviour of the usual two production factors of this type of models, technology and capital. However, he does that sequentially, therefore reducing the general scope of the model, as it is a special case of a broader version developed by David Romer [2001]. Romer’s general case analyse the dynamic behaviour more closely and, more importantly, allowing for a simultaneous analysis of the dynamics of the endogenous factors, which provide additional insights. The aim of this paper is to tackle the differences between the two endogenous models as an exercise to see expost exogenous shocks’ implications to the variables of interest. More specifically, in addition to the strictly theoretical analysis of some dynamic properties of the model, by programming difference equations in discrete time, one is also able to simulate and examine how the model will respond to shocks that one administer to it, on an ad-hoc basis – deterministic simulation.