EMaP: Explainable AI with Manifold-based Perturbations

In the last few years, many explanation methods based on the perturbations of input data have been introduced to improve our understanding of decisions made by black-box models. The goal of this work is to introduce a novel perturbation scheme so that more faithful and robust explanations can be obtained. Our study focuses on the impact of perturbing directions on the data topology. We show that perturbing along the orthogonal directions of the input manifold better preserves the data topology, both in the worst-case analysis of the discrete Gromov-Hausdorff distance and in the average-case analysis via persistent homology. From those results, we introduce EMaP algorithm, realizing the orthogonal perturbation scheme. Our experiments show that EMaP not only improves the explainers' performance but also helps them overcome a recently-developed attack against perturbation-based methods.Comment: 29 page

NeuCEPT: Locally Discover Neural Networks' Mechanism via Critical Neurons Identification with Precision Guarantee

Despite recent studies on understanding deep neural networks (DNNs), there exists numerous questions on how DNNs generate their predictions. Especially, given similar predictions on different input samples, are the underlying mechanisms generating those predictions the same? In this work, we propose NeuCEPT, a method to locally discover critical neurons that play a major role in the model's predictions and identify model's mechanisms in generating those predictions. We first formulate a critical neurons identification problem as maximizing a sequence of mutual-information objectives and provide a theoretical framework to efficiently solve for critical neurons while keeping the precision under control. NeuCEPT next heuristically learns different model's mechanisms in an unsupervised manner. Our experimental results show that neurons identified by NeuCEPT not only have strong influence on the model's predictions but also hold meaningful information about model's mechanisms.Comment: 6 main page

Spectral and Energy Efficiency Maximization for Content-Centric C-RANs with Edge Caching

This paper aims to maximize the spectral and energy efficiencies of a content-centric cloud radio access network (C-RAN), where users requesting the same contents are grouped together. Data are transferred from a central baseband unit to multiple remote radio heads (RRHs) equipped with local caches. The RRHs then send the received data to each group's user. Both multicast and unicast schemes are considered for data transmission. We formulate mixed-integer nonlinear problems in which user association, RRH activation, data rate allocation, and signal precoding are jointly designed. These challenging problems are subject to minimum data rate requirements, limited fronthaul capacity, and maximum RRH transmit power. Employing successive convex quadratic programming, we propose iterative algorithms with guaranteed convergence to Fritz John solutions. Numerical results confirm that the proposed joint designs markedly improve the spectral and energy efficiencies of the considered content-centric C-RAN compared to benchmark schemes. Importantly, they show that unicasting outperforms multicasting in terms of spectral efficiency in both cache and cache-less scenarios. In terms of energy efficiency, multicasting is the best choice for the system without cache whereas unicasting is best for the system with cache. Finally, edge caching is shown to improve both spectral and energy efficiencies.This work is supported in part by an ECRHDR scholarship from The University of Newcastle, in part by the Australian Research Council Discovery Project grants DP170100939 and DP160101537

Adjustment of Vietnamese labour market in time of economic fluctuations and structural changes

Dans cet article, nous examinons les ajustements du marché du travail aux fluctuations économiques, compte tenu des transformations structurelles en cours ainsi que des changements à court terme. Nous utilisons pour cela des données des recensements de la population ou publiées dans les annuaires statistiques de l’Office Général de la Statistique pour les séries à long terme, et les enquêtes emploi conduites entre 2007 à 2012 pour les données à court terme. Cet article souligne la profonde transformation du marché du travail au cours des dernières décennies. La population active a doublé en 25 ans et la part de l'agriculture est passée en dessous du seuil de 50 %. L’absorption de l'offre de travail a donc été l'un des principaux défis pour l'économie vietnamienne sur cette période. Le secteur des entreprises familiales agricoles et non-agricoles a été le principal pourvoyeur d'emplois au cours de ces années. Le marché du travail s'est adapté au récent ralentissement économique à travers différents canaux. Le chômage est resté stable mais le nombre de personnes inactives a augmenté. La quantité de travail a également été affectée par une réduction significative du nombre d'heures travaillées. Alors que le secteur non agricole a généré plus d'emplois pour les travailleurs qualifiés, un flux de travailleurs non-qualifiés vers l’agriculture a été observé. En raison de facteurs démographiques, l'absorption de l'offre de travail et la création de nouveaux emplois ne sont plus le principal problème. En revanche, l’évolution récente du marché du travail appelle à la mise en oeuvre de politiques structurelles en vue d’améliorer les conditions de travail, la période étant particulièrement favorable pour mener ces politiques puisque le Vietnam profite actuellement du dividende démographique

Energy-Efficient Design for Downlink Cloud Radio Access Networks

This work aims to maximize the energy efficiency of a downlink cloud radio access network (C-RAN), where data is transferred from a baseband unit in the core network to several remote radio heads via a set of edge routers over capacity-limited fronthaul links. The remote radio heads then send the received signals to their users via radio access links. We formulate a new mixed-integer nonlinear problem in which the ratio of network throughput and total power consumption is maximized. This challenging problem formulation includes practical constraints on routing, predefined minimum data rates, fronthaul capacity and maximum RRH transmit power. By employing the successive convex quadratic programming framework, an iterative algorithm is proposed with guaranteed convergence to a Fritz John solution of the formulated problem. Significantly, each iteration of the proposed algorithm solves only one simple convex program. Numerical examples with practical parameters confirm that the proposed joint optimization design markedly improves the C-RAN's energy efficiency compared to benchmark schemes.This work is supported in part by an ECR-HDR scholarship from The University of Newcastle, in part by the Australian Research Council Discovery Project grants DP170100939 and DP160101537, in part by Vietnam National Foundation for Science and Technology Development under grant number 101.02-2016.11 and in part by a startup fund from San Diego State University

D2D Communication Network with the Assistance of Power Beacon under the Impact of Co-channel Interferences and Eavesdropper: Performance Analysis

In this paper, we study and demonstrate the performance analysis of a device-to-device (D2D) com- munication network. Specifically, a source node trans- mits data to the destination node using the power bea- con’s harvested energy in order to overcome the limited energy budget. Besides, an eavesdropper located in the proximal region of a source is trying to overhear secure information. Notably, both eavesdropper and destina- tion are affected by co-channel interferences from other sources when they utilize the same frequency. By con- sidering the above discussions, we derived the closed- form expressions for outage probability (OP), intercept probability (IP), and secrecy outage probability (SOP) in connection with using the system model. The derived analytical expressions are then verified by utilizing both simulation and numerical results. Finally, the inten- sive parameters’ influences on the OP, IP, and SOP are also investigated