OpenRaiser/Intern-Atlas huggingface dataset:
Efficient data hashing with structured binary embeddings
Venue: arXiv cs.DS 2015
Year: 2015

We present here new mechanisms for hashing data via binary embeddings. Contrary to most of the techniques presented before, the embedding matrix of our mechanism is highly structured. That enables us to perform hashing more efficiently and use less memory. What is crucial and nonintuitive is the fact that imposing structured mechanism does not affect the quality of the produced hash. To the best of our knowledge, we are the first to give strong theoretical guarantees of the proposed binary hashing method by proving the efficiency of the mechanism for several classes of structured projection matrices. As a corollary, we obtain binary hashing mechanisms with strong concentration results for circulant and Topelitz matrices. Our approach is however much more general.
Schmitt-Trigger-based Recycling Sensor and Robust and High-Quality PUFs for Counterfeit IC Detection
Venue: arXiv cs.CR 2015
Year: 2015

We propose Schmitt-Trigger (ST) based recycling sensor that are tailored to amplify the aging mechanisms and detect fine grained recycling (minutes to seconds). We exploit the susceptibility of ST to process variations to realize high-quality arbiter PUF. Conventional SRAM PUF suffer from environmental fluctuation-induced bit flipping. We propose 8T SRAM PUF with a back-to-back PMOS latch to improve robustness by 4X. We also propose a low-power 7T SRAM with embedded Magnetic Tunnel Junction (MTJ) devices to enhance the robustness (2.3X to 20X).
APAC: Augmented PAttern Classification with Neural Networks
Venue: arXiv cs.CV 2015
Year: 2015

Deep neural networks have been exhibiting splendid accuracies in many of visual pattern classification problems. Many of the state-of-the-art methods employ a technique known as data augmentation at the training stage. This paper addresses an issue of decision rule for classifiers trained with augmented data. Our method is named as APAC: the Augmented PAttern Classification, which is a way of classification using the optimal decision rule for augmented data learning. Discussion of methods of data augmentation is not our primary focus. We show clear evidences that APAC gives far better generalization performance than the traditional way of class prediction in several experiments. Our convolutional neural network model with APAC achieved a state-of-the-art accuracy on the MNIST dataset among non-ensemble classifiers. Even our multilayer perceptron model beats some of the convolutional models with recently invented stochastic regularization techniques on the CIFAR-10 dataset.
Optimizing Ad Allocation in Social Advertising
Venue: arXiv cs.SI 2015
Year: 2015

Social advertising (or social promotion) is an effective approach that produces a significant cascade of adoption through influence in the online social networks. The goal of this work is to optimize the ad allocation from the platform's perspective. On the one hand, the platform would like to maximize revenue earned from each advertiser by exposing their ads to as many people as possible, one the other hand, the platform wants to reduce free-riding to ensure the truthfulness of the advertiser. To access this tradeoff, we adopt the concept of \emph{regret} \citep{viral2015social} to measure the performance of an ad allocation scheme. In particular, we study two social advertising problems: \emph{budgeted social advertising problem} and \emph{unconstrained social advertising problem}. In the first problem, we aim at selecting a set of seeds for each advertiser that minimizes the regret while setting budget constraints on the attention cost; in the second problem, we propose to optimize a linear combination of the regret and attention costs. We prove that both problems are NP-hard, and then develop a constant factor approximation algorithm for each problem.
Prefix-based Labeling Annotation for Effective XML Fragmentation
Venue: arXiv cs.DB 2015
Year: 2015

XML is gradually employed as a standard of data exchange in web environment since its inception in the 90s until present. It serves as a data exchange between systems and other applications. Meanwhile the data volume has grown substantially in the web and thus effective methods of storing and retrieving these data is essential. One recommended way is physically or virtually fragments the large chunk of data and distributes the fragments into different nodes. Fragmentation design of XML document contains of two parts: fragmentation operation and fragmentation method. The three fragmentation operations are Horizontal, Vertical and Hybrid. It determines how the XML should be fragmented. This paper aims to give an overview on the fragmentation design consideration and subsequently, propose a fragmentation technique using number addressing.
Dropshipping - alternative infrastructure of sales and promotion
Venue: arXiv cs.CY 2015
Year: 2015

An article about the transformation of the theory and practice of marketing in terms of e-commerce and network economy. The author considers Internet Marketing as an independent marketing communication in a virtual environment. The main thesis of the article: virtual environment determines the transformation of marketing, changing methods, priorities and structure not only practice, but also the theory of marketing.
Transformation of marketing in the e-commerce
Venue: arXiv cs.CY 2015
Year: 2015

The article is about transformation of the theory and practice of marketing in the conditions of e-commerce and network economy. The author considers Internet-marketing as an independent kind of marketing in the virtual communicative environment. The basic thesis of the article: the virtual environment defines marketing transformation, changing methods, priorities and structure at practice and then theories of marketing.
A Vision Based System for Monitoring the Loss of Attention in Automotive Drivers
Venue: arXiv cs.CV 2015
Year: 2015

On board monitoring of the alertness level of an automotive driver has been a challenging research in transportation safety and management. In this paper, we propose a robust real time embedded platform to monitor the loss of attention of the driver during day as well as night driving conditions. The PERcentage of eye CLOSure (PERCLOS) has been used as the indicator of the alertness level. In this approach, the face is detected using Haar like features and tracked using a Kalman Filter. The Eyes are detected using Principal Component Analysis (PCA) during day time and the block Local Binary Pattern (LBP) features during night. Finally the eye state is classified as open or closed using Support Vector Machines(SVM). In plane and off plane rotations of the drivers face have been compensated using Affine and Perspective Transformation respectively. Compensation in illumination variation is carried out using Bi Histogram Equalization (BHE). The algorithm has been cross validated using brain signals and finally been implemented on a Single Board Computer (SBC) having Intel Atom processor, 1 GB RAM, 1.66 GHz clock, x86 architecture, Windows Embedded XP operating system. The system is found to be robust under actual driving conditions.
An Image is Worth More than a Thousand Favorites: Surfacing the Hidden Beauty of Flickr Pictures
Venue: arXiv cs.SI 2015
Year: 2015

The dynamics of attention in social media tend to obey power laws. Attention concentrates on a relatively small number of popular items and neglecting the vast majority of content produced by the crowd. Although popularity can be an indication of the perceived value of an item within its community, previous research has hinted to the fact that popularity is distinct from intrinsic quality. As a result, content with low visibility but high quality lurks in the tail of the popularity distribution. This phenomenon can be particularly evident in the case of photo-sharing communities, where valuable photographers who are not highly engaged in online social interactions contribute with high-quality pictures that remain unseen. We propose to use a computer vision method to surface beautiful pictures from the immense pool of near-zero-popularity items, and we test it on a large dataset of creative-commons photos on Flickr. By gathering a large crowdsourced ground truth of aesthetics scores for Flickr images, we show that our method retrieves photos whose median perceived beauty score is equal to the most popular ones, and whose average is lower by only 1.5%.
Reporting, Reviewing, and Responding to Harassment on Twitter
Venue: arXiv cs.SI 2015
Year: 2015

When people experience harassment online, from individual threats or invective to coordinated campaigns of harassment, they have the option to report the harassers and content to the platform where the harassment has occurred. Platforms then evaluate harassment reports against terms of use and other policies to decide whether to remove content or take action against the alleged harasser--or not. On Twitter, harassing accounts can be deleted entirely, suspended (with content made unavailable pending appeal or specific changes), or sent a warning. Some platforms, including Twitter and YouTube, grant authorized reporters or trusted flaggers special privileges to identify and report inappropriate content on behalf of others. In November 2014, Twitter granted Women, Action, and the Media (WAM!) this authorized reporter status. In three weeks, WAM! reviewers assessed 811 incoming reports of harassment and escalated 161 reports to Twitter, ultimately seeing Twitter carry out 70 account suspensions, 18 warnings, and one deleted account. This document presents findings from this three-week project; it draws on both quantitative and qualitative methods. Findings focus on the people reporting and receiving harassment, the kinds of harassment that were reported, Twitter's response to harassment reports, the process of reviewing harassment reports, and challenges for harassment reporting processes.
Laws governing development of institutionalization of e-commerce
Venue: arXiv cs.CY 2015
Year: 2015

Article about objective laws of formation of social and economic institutes in system of electronic commerce. Rapid development of Internet technologies became the reason of deep institutional transformation of economic relations. The author analyzes value transaction costs as motive power of formation of new economic institutes in network economy.
Priorities of institutional regulation of e-commerce: Russia and world trends
Venue: arXiv cs.CY 2015
Year: 2015

E-commerce is gradually transformed from a version of trading activity to independent branch of global network economy which cannot be ignored. The Russian Federation is in the lead in the CIS on development of e-commerce, but lags behind world leaders in institutionalization of e-commerce. Problems of state regulation of e-commerce in Russia are analyzed in article, ways of their decision are offered.
Transformation of chains of deliveries in network economy: priorities and prospects
Venue: arXiv cs.CY 2015
Year: 2015

Development of network economy changes the institutional maintenance of economic relations. On change to traditional channels of distribution virtual networks of distribution of production come. In article features and mechanisms of transformation of chains deliveries in e-commerce reveal.
Pose Graph Optimization in the Complex Domain: Lagrangian Duality, Conditions For Zero Duality Gap, and Optimal Solutions
Venue: arXiv cs.RO 2015
Year: 2015

Pose Graph Optimization (PGO) is the problem of estimating a set of poses from pairwise relative measurements. PGO is a nonconvex problem, and currently no known technique can guarantee the computation of an optimal solution. In this paper, we show that Lagrangian duality allows computing a globally optimal solution, under certain conditions that are satisfied in many practical cases. Our first contribution is to frame the PGO problem in the complex domain. This makes analysis easier and allows drawing connections with the recent literature on unit gain graphs. Exploiting this connection we prove non-trival results about the spectrum of the matrix underlying the problem. The second contribution is to formulate and analyze the dual problem in the complex domain. Our analysis shows that the duality gap is connected to the number of eigenvalues of the penalized pose graph matrix, which arises from the solution of the dual. We prove that if this matrix has a single eigenvalue in zero, then (i) the duality gap is zero, (ii) the primal PGO problem has a unique solution, and (iii) the primal solution can be computed by scaling an eigenvector of the penalized pose graph matrix. The third contribution is algorithmic: we exploit the dual problem and propose an algorithm that computes a guaranteed optimal solution for PGO when the penalized pose graph matrix satisfies the Single Zero Eigenvalue Property (SZEP). We also propose a variant that deals with the case in which the SZEP is not satisfied. The fourth contribution is a numerical analysis. Empirical evidence shows that in the vast majority of cases (100% of the tests under noise regimes of practical robotics applications) the penalized pose graph matrix does satisfy the SZEP, hence our approach allows computing the global optimal solution. Finally, we report simple counterexamples in which the duality gap is nonzero, and discuss open problems.
A Family of Erasure Correcting Codes with Low Repair Bandwidth and Low Repair Complexity
Venue: arXiv cs.IT 2015
Year: 2015

We present the construction of a new family of erasure correcting codes for distributed storage that yield low repair bandwidth and low repair complexity. The construction is based on two classes of parity symbols. The primary goal of the first class of symbols is to provide good erasure correcting capability, while the second class facilitates node repair, reducing the repair bandwidth and the repair complexity. We compare the proposed codes with other codes proposed in the literature.
Investigating the Cost of Anonymity on Dynamic Networks
Venue: arXiv cs.DC 2015
Year: 2015

In this paper we study the difficulty of counting nodes in a synchronous dynamic network where nodes share the same identifier, they communicate by using a broadcast with unlimited bandwidth and, at each synchronous round, network topology may change. To count in such setting, it has been shown that the presence of a leader is necessary. We focus on a particularly interesting subset of dynamic networks, namely \textit{Persistent Distance} - ${\cal G}($PD$)_{h}$, in which each node has a fixed distance from the leader across rounds and such distance is at most $h$. In these networks the dynamic diameter $D$ is at most $2h$. We prove the number of rounds for counting in ${\cal G}($PD$)_{2}$ is at least logarithmic with respect to the network size $|V|$. Thanks to this result, we show that counting on any dynamic anonymous network with $D$ constant w.r.t. $|V|$ takes at least $D+ Ω(\text{log}\, |V| )$ rounds where $Ω(\text{log}\, |V|)$ represents the additional cost to be payed for handling anonymity. At the best of our knowledge this is the fist non trivial, i.e. different from $Ω(D)$, lower bounds on counting in anonymous interval connected networks with broadcast and unlimited bandwith.
Parallelism and Synchronization in an Infinitary Context (Long Version)
Venue: arXiv cs.LO 2015
Year: 2015

We study multitoken interaction machines in the context of a very expressive logical system with exponentials, fixpoints and synchronization. The advantage of such machines is to provide models in the style of the Geometry of Interaction, i.e., an interactive semantics which is close to low-level implementation. On the one hand, we prove that despite the inherent complexity of the framework, interaction is guaranteed to be deadlock free. On the other hand, the resulting logical system is powerful enough to embed PCF and to adequately model its behaviour, both when call-by-name and when call-by-value evaluation are considered. This is not the case for single-token stateless interactive machines.
Predicting Occupancy Trends in Barcelona's Bicycle Service Stations Using Open Data
Venue: arXiv cs.AI 2015
Year: 2015

In 2008, the CEO of the company that manages and maintains the public bicycle service in Barcelona recognized that one may not expect to always find a place to leave the rented bike nearby their destination, similarly to the case when, driving a car, people may not find a parking lot. In this work, we make predictions about the statuses of the stations of the public bicycle service in Barcelona. We show that it is feasible to correctly predict nearly half of the times when the stations are either completely full of bikes or completely empty, up to 2 days before they actually happen. That is, users might avoid stations at times when they could not return a bicycle that they have rented before, or when they would not find a bike to rent. To achieve that, we apply the Random Forest algorithm to classify the status of the stations and improve the lifetime of the models using publicly available data, such as information about the weather forecast. Finally, we expect that the results of the predictions can be used to improve the quality of the service and make it more reliable for the users.
Informetric Analyses of Knowledge Organization Systems (KOSs)
Venue: arXiv cs.DL 2015
Year: 2015

A knowledge organization system (KOS) is made up of concepts and semantic relations between the concepts which represent a knowledge domain terminologically. We distinguish between five approaches to KOSs: nomenclatures, classification systems, thesauri, ontologies and, as a borderline case of KOSs, folksonomies. The research question of this paper is: How can we informetrically analyze the effectiveness of KOSs? Quantitative informetric measures and indicators allow for the description, for comparative analyses as well as for evaluation of KOSs and their quality. We describe the state of the art of KOS evaluation. Most of the evaluation studies found in the literature are about ontologies. We introduce measures of the structure of KOSs (e.g., groundedness, tangledness, fan-out factor, or granularity) and indicators of KOS quality (completeness, consistency, overlap, and use).
A PCA-Based Convolutional Network
Venue: arXiv cs.LG 2015
Year: 2015

In this paper, we propose a novel unsupervised deep learning model, called PCA-based Convolutional Network (PCN). The architecture of PCN is composed of several feature extraction stages and a nonlinear output stage. Particularly, each feature extraction stage includes two layers: a convolutional layer and a feature pooling layer. In the convolutional layer, the filter banks are simply learned by PCA. In the nonlinear output stage, binary hashing is applied. For the higher convolutional layers, the filter banks are learned from the feature maps that were obtained in the previous stage. To test PCN, we conducted extensive experiments on some challenging tasks, including handwritten digits recognition, face recognition and texture classification. The results show that PCN performs competitive with or even better than state-of-the-art deep learning models. More importantly, since there is no back propagation for supervised finetuning, PCN is much more efficient than existing deep networks.
Sustainability in Software Product Lines: Report on Discussion Panel at SPLC 2014
Venue: arXiv cs.SE 2015
Year: 2015

Sustainability (defined as 'the capacity to keep up') encompasses a wide set of aims: ranging from energy efficient software products (environmental sustainability), reduction of software development and maintenance costs (economic sustainability), to employee and end-user wellbeing (social sustainability). In this report we explore the role that sustainability plays in software product line engineering (SPL). The report is based on the 'Sustainability in Software Product Lines' panel held at SPLC 2014.
Rank diversity of languages: Generic behavior in computational linguistics
Venue: arXiv cs.CL 2015
Year: 2015

Statistical studies of languages have focused on the rank-frequency distribution of words. Instead, we introduce here a measure of how word ranks change in time and call this distribution \emph{rank diversity}. We calculate this diversity for books published in six European languages since 1800, and find that it follows a universal lognormal distribution. Based on the mean and standard deviation associated with the lognormal distribution, we define three different word regimes of languages: "heads" consist of words which almost do not change their rank in time, "bodies" are words of general use, while "tails" are comprised by context-specific words and vary their rank considerably in time. The heads and bodies reflect the size of language cores identified by linguists for basic communication. We propose a Gaussian random walk model which reproduces the rank variation of words in time and thus the diversity. Rank diversity of words can be understood as the result of random variations in rank, where the size of the variation depends on the rank itself. We find that the core size is similar for all languages studied.
Distributed House-Hunting in Ant Colonies
Venue: arXiv cs.DC 2015
Year: 2015

We introduce the study of the ant colony house-hunting problem from a distributed computing perspective. When an ant colony's nest becomes unsuitable due to size constraints or damage, the colony must relocate to a new nest. The task of identifying and evaluating the quality of potential new nests is distributed among all ants. The ants must additionally reach consensus on a final nest choice and the full colony must be transported to this single new nest. Our goal is to use tools and techniques from distributed computing theory in order to gain insight into the house-hunting process. We develop a formal model for the house-hunting problem inspired by the behavior of the Temnothorax genus of ants. We then show a Ω(log n) lower bound on the time for all n ants to agree on one of k candidate nests. We also present two algorithms that solve the house-hunting problem in our model. The first algorithm solves the problem in optimal O(log n) time but exhibits some features not characteristic of natural ant behavior. The second algorithm runs in O(k log n) time and uses an extremely simple and natural rule for each ant to decide on the new nest.
Non-unique games over compact groups and orientation estimation in cryo-EM
Venue: arXiv cs.CV 2015
Year: 2015

Let $\mathcal{G}$ be a compact group and let $f_{ij} \in L^2(\mathcal{G})$. We define the Non-Unique Games (NUG) problem as finding $g_1,\dots,g_n \in \mathcal{G}$ to minimize $\sum_{i,j=1}^n f_{ij} \left( g_i g_j^{-1}\right)$. We devise a relaxation of the NUG problem to a semidefinite program (SDP) by taking the Fourier transform of $f_{ij}$ over $\mathcal{G}$, which can then be solved efficiently. The NUG framework can be seen as a generalization of the little Grothendieck problem over the orthogonal group and the Unique Games problem and includes many practically relevant problems, such as the maximum likelihood estimator} to registering bandlimited functions over the unit sphere in $d$-dimensions and orientation estimation in cryo-Electron Microscopy.
Mismatched Estimation in Large Linear Systems
Venue: arXiv cs.IT 2015
Year: 2015

We study the excess mean square error (EMSE) above the minimum mean square error (MMSE) in large linear systems where the posterior mean estimator (PME) is evaluated with a postulated prior that differs from the true prior of the input signal. We focus on large linear systems where the measurements are acquired via an independent and identically distributed random matrix, and are corrupted by additive white Gaussian noise (AWGN). The relationship between the EMSE in large linear systems and EMSE in scalar channels is derived, and closed form approximations are provided. Our analysis is based on the decoupling principle, which links scalar channels to large linear system analyses. Numerical examples demonstrate that our closed form approximations are accurate.