Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks

Deep neural networks have emerged as a widely used and effective means for tackling complex, real-world problems. However, a major obstacle in applying them to safety-critical systems is the great difficulty in providing formal guarantees about their behavior. We present a novel, scalable, and efficient technique for verifying properties of deep neural networks (or providing counter-examples). The technique is based on the simplex method, extended to handle the non-convex Rectified Linear Unit (ReLU) activation function, which is a crucial ingredient in many modern neural networks. The verification procedure tackles neural networks as a whole, without making any simplifying assumptions. We evaluated our technique on a prototype deep neural network implementation of the next-generation airborne collision avoidance system for unmanned aircraft (ACAS Xu). Results show that our technique can successfully prove properties of networks that are an order of magnitude larger than the largest networks verified using existing methods.Comment: This is the extended version of a paper with the same title that appeared at CAV 201

Data Processing and the Envision

Data is being generated very rapidly due to increase in information in everyday life. Huge amount of data gets accumulated from various organizations that is difficult to analyze and exploit. Data created by an expanding number of sensors in the environment such as traffic cameras and satellites, internet activities on social networking sites, healthcare database, government database, sales data etc., are example of huge data. Processing, analyzing and communicating this data are a challenge. Online shopping websites get flooded with voluminous amount of sales data every day. Analyzing and visualizing this data for information retrieval is a difficult task. There are large number of information visualization techniques which have been developed over the last decade to support the exploration of large data sets. With today’s data management systems, it is only possible to view quite small portions of the data. If the data is presented textually, the amount of data which can be displayed is in the range of some 100 data items, but this is like a drop in the ocean when dealing with data sets containing millions of data items. Data is being generated very rapidly due to increase in information in everyday life. Huge amount of data gets accumulated from various organizations that is difficult to analyze and exploit. Data created by an expanding number of sensors in the environment such as traffic cameras and satellites, internet activities on social networking sites, healthcare database, government database, sales data etc., are example of huge data. Processing, analyzing and communicating this data are a challenge. Online shopping websites get flooded with voluminous amount of sales data every day. Analyzing and visualizing this data for information retrieval is a difficult task. Therefore, a system is required which will effectively analyze and visualize data. This paper focuses on a system which will visualize sales data which will help users in applying intelligence in business, revenue generation, and decision making, managing business operation and tracking progress of tasks. Effective and efficient data visualization is the key part of the discovery process. It is the intermediate between the human intuition and quantitative context of the data, thus an essential component of the scientific path from data into knowledge and understanding. Therefore, a system is required which will effectively analyze and visualize data. This paper focuses on a system which will visualize data which will help users in interactive data visualization applying in business, revenue generation, and decision making, managing business operation and tracking progress of tasks

Optimisation d'un hélicoptère tandem pour la surveillance maritime avec des rotors à vitesse variable

L'utilisation d'avions non-pilotés est une solution éprouvée dans le domaine de la surveillance maritime. Toutefois, l'utilisation d'hélicoptères non-pilotés est maintenant une alternative convoitée grâce aux bénéfices du décollage et de l'atterrissage vertical. Ces bénéfices permettent d'intégrer l'opération de l'aéronef au navire lui-même, permettant ainsi un déploiement immédiat. Le critère de performance le plus critique lors d'une mission de surveillance maritime est l'endurance, c'est-à-dire le temps de vol maximal de l'aéronef. De façon intrinsèque à leur principe de fonctionnement, les hélicoptères offrent une moins grande endurance que les avions. Il y a donc un intérêt majeur à améliorer l'autonomie de vol d'un hélicoptère lors d'une opération de surveillance maritime. Un concept prometteur pour augmenter l'endurance d'un hélicoptère est de diminuer la vitesse d'opération du rotor en plein vol. Ce mémoire présente les bénéfices potentiels de coupler le concept de rotor à vitesse variable avec un moteur à allumage commandé (gasoline) ou par compression (diesel). Jusqu'à maintenant, cette combinaison n'a pas été étudiée dans la littérature. Les études se sont plutôt limitées aux turbines à gaz, ce qui résulte en des effets conflictuels liés à la chute d'efficacité lors de la diminution de la vitesse d'opération. L'efficacité quasi-constante des moteurs à pistons permettrait donc de profiter du plein potentiel du concept de rotor à vitesse variable. Pour ce faire, un modèle de performance d'hélicoptère tandem est développé et validé expérimentalement avec le LX300 de Laflamme Aéro. Deux configurations du LX300 sont étudiées, soit l'une équipée d'un moteur à allumage par étincelle et l'autre par compression, et sont comparées. Il est démontré que la configuration du LX300 incorporant un moteur à allumage par compression bénéficie de gains plus importants que la configuration avec moteur à allumage par étincelle. Les bénéfices sont particulièrement intéressants pour des vols à grande capacité de carburant où jusqu'à 25% et 19% d'augmentation en autonomie et en rayon d'action sont réalisables respectivement pour la configuration diesel. La configuration équipée d'un moteur gasoline quant à elle offre des gains de 15% et 6% en autonomie et rayon d'action respectivement. La combinaison du concept de rotor à vitesse variable et d'un moteur à allumage par étincelle ou compression est donc une avenue prometteuse pour améliorer la performance d'hélicoptères non-pilotés pour accomplir des missions de surveillance maritime. Ces gains de performances se transfèrent aussi pour des missions de transport de charge lourde sur de longues distances

Hillview:A trillion-cell spreadsheet for big data

Hillview is a distributed spreadsheet for browsing very large datasets that cannot be handled by a single machine. As a spreadsheet, Hillview provides a high degree of interactivity that permits data analysts to explore information quickly along many dimensions while switching visualizations on a whim. To provide the required responsiveness, Hillview introduces visualization sketches, or vizketches, as a simple idea to produce compact data visualizations. Vizketches combine algorithmic techniques for data summarization with computer graphics principles for efficient rendering. While simple, vizketches are effective at scaling the spreadsheet by parallelizing computation, reducing communication, providing progressive visualizations, and offering precise accuracy guarantees. Using Hillview running on eight servers, we can navigate and visualize datasets of tens of billions of rows and trillions of cells, much beyond the published capabilities of competing systems

Rapid Sampling for Visualizations with Ordering Guarantees

Visualizations are frequently used as a means to understand trends and gather insights from datasets, but often take a long time to generate. In this paper, we focus on the problem of rapidly generating approximate visualizations while preserving crucial visual proper- ties of interest to analysts. Our primary focus will be on sampling algorithms that preserve the visual property of ordering; our techniques will also apply to some other visual properties. For instance, our algorithms can be used to generate an approximate visualization of a bar chart very rapidly, where the comparisons between any two bars are correct. We formally show that our sampling algorithms are generally applicable and provably optimal in theory, in that they do not take more samples than necessary to generate the visualizations with ordering guarantees. They also work well in practice, correctly ordering output groups while taking orders of magnitude fewer samples and much less time than conventional sampling schemes.Comment: Tech Report. 17 pages. Condensed version to appear in VLDB Vol. 8 No.

Regionalisation and cross-region integration. Twin dynamics in the automotive international trade networks

The paper analyses the changes that occurred over 25 years in the geography of trade in automotive parts and components. Using the Infomap multilayer clustering algorithm, we identify clusters of countries and their specific trades in the automotive international trade network, we measure the relative importance of each cluster and the interconnections between them, and we analyse the contribution of countries and of trade of components and parts in the clusters. The analysis highlights the formation of denser and more hierarchical networks generated by Germany's trade relations with EU countries and by the US preferential trade agreements with Canada and Mexico, as well as the surge of China. While the relative importance of the main clusters and of some individual countries change significantly, connections between clusters increase over time