nils-herrmann/clean_scirepeval huggingface dataset:
Customer Lifetime Value Prediction Using Embeddings

We describe the Customer LifeTime Value (CLTV) prediction system deployed at ASOS.com, a global online fashion retailer. CLTV prediction is an important problem in e-commerce where an accurate estimate of future value allows retailers to effectively allocate marketing spend, identify and nurture high value customers and mitigate exposure to losses. The system at ASOS provides daily estimates of the future value of every customer and is one of the cornerstones of the personalised shopping experience. The state of the art in this domain uses large numbers of handcrafted features and ensemble regressors to forecast value, predict churn and evaluate customer loyalty. Recently, domains including language, vision and speech have shown dramatic advances by replacing handcrafted features with features that are learned automatically from data. We detail the system deployed at ASOS and show that learning feature representations is a promising extension to the state of the art in CLTV modelling. We propose a novel way to generate embeddings of customers, which addresses the issue of the ever changing product catalogue and obtain a significant improvement over an exhaustive set of handcrafted features.
Multimodal 'eyes-free' interaction techniques for wearable devices

Mobile and wearable computers present input/output prob-lems due to limited screen space and interaction techniques. When mobile, users typically focus their visual attention on navigating their environment - making visually demanding interface designs hard to operate. This paper presents two multimodal interaction techniques designed to overcome these problems and allow truly mobile, 'eyes-free' device use. The first is a 3D audio radial pie menu that uses head gestures for selecting items. An evaluation of a range of different audio designs showed that egocentric sounds re-duced task completion time, perceived annoyance, and al-lowed users to walk closer to their preferred walking speed. The second is a sonically enhanced 2D gesture recognition system for use on a belt-mounted PDA. An evaluation of the system with and without audio feedback showed users' ges-tures were more accurate when dynamically guided by au-dio-feedback. These novel interaction techniques demon-strate effective alternatives to visual-centric interface de-signs on mobile devices.
Linear N-Point Camera Pose Determination

ÐThe determination of camera position and orientation from known correspondences of 3D reference points and their images is known as pose estimation in computer vision and space resection in photogrammetry. It is wellknown that from three corresponding points there are at most four algebraic solutions. Less appears to be known about the cases of four and five corresponding points. In this paper, we propose a family of linear methods that yield a unique solution to 4and 5-point pose determination for generic reference points. We first review the 3-point algebraic method. Then we present our twostep, 4-point and one-step, 5-point linear algorithms. The 5-point method can also be extended to handle more than five points. Finally, we demonstrate our methods on both simulated and real images. We show that they do not degenerate for coplanar configurations and even outperform the special linear algorithm for coplanar configurations in practice. Index TermsÐPose estimation, space resection, 2D-3D image orientation, exterior orientation determination, perspective-n-point-problem, four points, five points.
Denial-of-service attack-detection techniques

Denial-of-service (DoS) detection techniques - such as activity profiling, change-point detection, and wavelet-based signal analysis - face the considerable challenge of discriminating network-based flooding attacks from sudden increases in legitimate activity or flash events. This survey of techniques and testing results provides insight into our ability to successfully identify DoS flooding attacks. Although each detector shows promise in limited testing, none completely solve the detection problem. Combining various approaches with experienced network operators most likely produce the best results.
On the Margin Theory of Feedforward Neural Networks

Past works have shown that, somewhat surprisingly, over-parametrization can help generalization in neural networks. Towards explaining this phenomenon, we adopt a margin-based perspective.  for multilayer feedforward relu networks, the global minimizer of a weakly-regularized cross-entropy loss has the maximum normalized margin among all networks, 2) as a result, increasing the over-parametrization improves the normalized margin and generalization error bounds for two-layer networks. In particular, an infinite-size neural network enjoys the best generalization guarantees. The typical infinite feature methods are kernel methods; we compare the neural net margin with that of kernel methods and construct natural instances where kernel methods have much weaker generalization guarantees. We validate this gap between the two approaches empirically. Finally, this infinite-neuron viewpoint is also fruitful for analyzing optimization. We show that a perturbed gradient flow on infinite-size networks finds a global optimizer in polynomial time.
Designing mobility models based on social network theory

Validation of mobile ad hoc network protocols relies almost exclusively on simulation. The value of the validation is, therefore, highly dependent on how realistic the movement models used in the simulations are. Since there is a very limited number of available real traces in the public domain, synthetic models for movement pattern generation must be used. However, most widely used models are currently very simplistic, their focus being ease of implementation rather than soundness of foundation. Simulation results of protocols are often based on randomly generated movement patterns and, therefore, may differ considerably from those that can be obtained by deploying the system in real scenarios. Movement is strongly affected by the needs of humans to socialise or cooperate, in one form or another. Fortunately, humans are known to associate in particular ways that can be mathematically modelled and that have been studied in social sciences for years.
 In this paper we propose a new mobility model founded on social network theory. The model allows collections of hosts to be grouped together in a way that is based on social relationships among the individuals. This clustering is then mapped to a topographical space, with movements influenced by the strength of social ties that may also change in time. We have validated our model with real traces by showing that the synthetic mobility traces are a very good approximation of human movement patterns. The impact of the adoption of the proposed algorithm on the performance of AODV and DSR is also presented and discussed.
A Fully Integrated Reconfigurable Self-Startup RF Energy-Harvesting System With Storage Capability

This paper introduces a fully integrated RF energy-harvesting system. The system can simultaneously deliver the current demanded by external dc loads and store the extra energy in external capacitors, during periods of extra output power. The design is fabricated in 0.18- $\mu \text{m}$  CMOS technology, and the active chip area is 1.08 mm2. The proposed self-startup system is reconfigurable with an integrated LC matching network, an RF rectifier, and a power management/controller unit, which consumes 66–157 nW. The required clock generation and the voltage reference circuit are integrated on the same chip. Duty cycle control is used to operate for the low input power that cannot provide the demanded output power. Moreover, the number of stages of the RF rectifier is reconfigurable to increase the efficiency of the available output power. For high available power, a secondary path is activated to charge an external energy storage element. The measured RF input power sensitivity is −14.8 dBm at a 1-V dc output.
Exploration-exploitation tradeoff using variance estimates in multi-armed bandits

Algorithms based on upper confidence bounds for balancing exploration and exploitation are gaining popularity since they are easy to implement, efficient and effective. This paper considers a variant of the basic algorithm for the stochastic, multi-armed bandit problem that takes into account the empirical variance of the different arms. In earlier experimental works, such algorithms were found to outperform the competing algorithms. We provide the first analysis of the expected regret for such algorithms. As expected, our results show that the algorithm that uses the variance estimates has a major advantage over its alternatives that do not use such estimates provided that the variances of the payoffs of the suboptimal arms are low. We also prove that the regret concentrates only at a polynomial rate. This holds for all the upper confidence bound based algorithms and for all bandit problems except those special ones where with probability one the payoff obtained by pulling the optimal arm is IThis research was funded in part by the National Science and Engineering Research Council (NSERC), iCore and the Alberta Ingenuity Fund. ∗Corresponding author. Email addresses: audibert@certis.enpc.fr (Jean Yves Audibert), remi.munos@inria.fr (Rémi Munos), szepesva@cs.ualberta.ca (Csaba Szepesvári) 1Csaba Szepesvári is on leave from MTA SZTAKI, Budapest, Hungary.  2008 larger than the expected payoff for the second best arm. Hence, although upper confidence bound bandit algorithms achieve logarithmic expected regret rates, they might not be suitable for a risk-averse decision maker. We illustrate some of the results by computer simulations.
Algebraic Distance on Graphs

Measuring the connection strength between a pair of vertices in a graph is one of the most important concerns in many graph applications. Simple measures such as edge weights may not be sufficient for capturing the effects associated with short paths of lengths greater than one. In this paper, we consider an iterative process that smooths an associated value for nearby vertices, and we present a measure of the local connection strength (called the algebraic distance, see ) based on this process. The proposed measure is attractive in that the process is simple, linear, and easily parallelized. An analysis of the convergence property of the process reveals that the local neighborhoods play an important role in determining the connectivity between vertices. We demonstrate the practical effectiveness of the proposed measure through several combinatorial optimization problems on graphs and hypergraphs.
HOW MUCH DOES INDUSTRY MATTER , REALLY ?

In this paper, we examine the importance of year, industry, corporate-parent, and businessspecific effects on the profitability of U.S. public corporations within specific 4-digit SIC categories. Our results indicate that year, industry, corporate-parent, and business-specific effects account for 2 percent, 19 percent, 4 percent, and 32 percent, respectively, of the aggregate variance in profitability. We also find that the importance of the effects differs substantially across broad economic sectors. Industry effects account for a smaller portion of profit variance in manufacturing but a larger portion in lodging/entertainment, services, wholesale/retail trade, and transportation. Across all sectors we find a negative covariance between corporate-parent and industry effects. A detailed analysis suggests that industry, corporate-parent, and business-specific effects are related in complex ways.
Metamaterial-Based Antennas: Research and Developments

A brief review of metamaterials and their applications to antenna systems is given. Artificial magnetic conductors and electrically small radiating and scattering systems are emphasized. Single negative, double negative, and zero-index metamaterial systems are discussed as a means to manipulate their size, efficiency, bandwidth, and directivity characteristics. key words: metamaterials, electrically small antennas, complex media, artificial magnetic conductors
Guidelines for reporting of health interventions using mobile phones: mobile health (mHealth) evidence reporting and assessment (mERA) checklist.

1 1Johns Hopkins Bloomberg School of Public Health, Department of International Health, Baltimore, MD 21205, USA 2Johns Hopkins University, Global mHealth Initiative, Baltimore 3Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA 4Family Health International 360, Durham, NC, USA 5School of Nursing and Health Professions, University of San Francisco, San Francisco, CA, USA 6World Health Organization, Department of Reproductive Health and Research, Geneva, Switzerland 7International Development Research Centre, Ottawa, Canada Correspondence to: A Labrique alabriq1@jhu.edu Additional material is published online only. To view please visit the journal online. Cite this as: BMJ 2016;352:i1174 http://dx.doi.org/10.1136/bmj.i1174
Structure extraction from texture via relative total variation

It is ubiquitous that meaningful structures are formed by or appear over textured surfaces. Extracting them under the complication of texture patterns, which could be regular, near-regular, or irregular, is very challenging, but of great practical importance. We propose new inherent variation and relative total variation measures, which capture the essential difference of these two types of visual forms, and develop an efficient optimization system to extract main structures. The new variation measures are validated on millions of sample patches. Our approach finds a number of new applications to manipulate, render, and reuse the immense number of "structure with texture" images and drawings that were traditionally difficult to be edited properly.
Chinese Word Segmentation and Named Entity Recognition: A Pragmatic Approach

This article presents a pragmatic approach to Chinese word segmentation. It differs from most previous approaches mainly in three respects. First, while theoretical linguists have defined Chinese words using various linguistic criteria, Chinese words in this study are defined pragmatically as segmentation units whose definition depends on how they are used and processed in realistic computer applications. Second, we propose a pragmatic mathematical framework in which segmenting known words and detecting unknown words of different types (i.e., morphologically derived words, factoids, named entities, and other unlisted words) can be performed simultaneously in a unified way. These tasks are usually conducted separately in other systems. Finally, we do not assume the existence of a universal word segmentation standard that is application-independent. Instead, we argue for the necessity of multiple segmentation standards due to the pragmatic fact that different natural language processing applications might require different granularities of Chinese words. These pragmatic approaches have been implemented in an adaptive Chinese word segmenter, called MSRSeg, which will be described in detail. It consists of two components: (1) a generic segmenter that is based on the framework of linear mixture models and provides a unified approach to the five fundamental features of word-level Chinese language processing: lexicon word processing, morphological analysis, factoid detection, named entity recognition, and new word identification; and (2) a set of output adaptors for adapting the output of (1) to different application-specific standards. Evaluation on five test sets with different standards shows that the adaptive system achieves state-of-the-art performance on all the test sets.
Real time video stabilization for handheld devices

The paper proposes a method and robust algorithm for 2D video stabilization designed for portable devices in real-time. The BSC (Boundary Signal Computation) chip of TI (Texas Instruments) is essentially used (or emulated herein) for searching of correlations between the 1D integral projections, horizontal and vertical ones, by a SAD (Sums of Absolute Differences) approach. The proposed method is based on an accurate vector model allowing interpretations of increasing complexity for the transformations among frames. Experiments, conducted on testing video clips, are very promising for the future R&D of the method.
Minimum-Perimeter Enclosing k-gon

Let P = p1, . . . , pn be a simple polygon (all polygons are assumed convex throughout this paper). A fundamental problem in geometric optimization is to compute a minimum-area or a minimum-perimeter convex k-gon (denoted QA or Qp, resp.) that encloses P . While efficient algorithms for finding QA are known for more than 20 years [8, 1, 2], the problem of finding Qp has remained open; the problem is posed as open in [3, 6, 7, 9, 12, 14, 5]. 1 Chang and Yap  give a comprehensive classification of the incluson/enclosure problems, but do not mention the minimum-perimeter enclosing kgon problem (Enc(Pall, Pk, perimeter), in their terminology) at all. We give the first polynomial-time algorithms for computing Qp. In order to obtain our solution, we prove a structural result about an optimal polygon: Local optimality implies that it is “flush” with P (Lemma 1). As a by-product we obtain an algorithm for finding the minimum-perimeter “envelope” — a convex k-gon with a specified sequence of interior angles. Our proofs are very simple and are based on elementary geometry.2 The exact coordinates of the vertices of Qp are given by the roots of high-degree polynomials. In general, it is impossible to find the coordinates exactly in polynomial time . Thus, given ε > 0 as a part of the input to the problem, we will be satisfied with a (1 + ε)-approximate solution. Finding Qp Our algorithm is based on the following lemma, whose (simple) proof we defer until the next paragraph: Lemma 1. Qp is flush with P , i.e., one of the edges of Qp contains an edge of P . By Lemma 1, we may consider each edge of P as a candidate flush edge with Qp and turn the scene into simple polygon P . This reduces finding Qp to solving n instances of the problem of finding a shortest (k + 1)-link path in simple polygon P , a problem which can be solved in polynomial time . Thus we have our main result: Theorem 2. Qp can be found in polynomial time.
1 Multiresolution Signal Decomposition Schemes . Part 2 : Morphological Wavelets

In its original form, the wavelet transform is a linear tool. However, it has been increasingly recognized that nonlinear extensions are possible. A major impulse to the development of nonlinear wavelet transforms has been given by the introduction of the lifting scheme by Sweldens. The aim of this report, which is a sequel to a previous report devoted exclusively to the pyramid transform, is to present an axiomatic framework encompassing most existing linear and nonlinear wavelet decompositions. Furthermore, it introduces some, thus far unknown, wavelets based on mathematical morphology, such as the morphological Haar wavelet, both in one and two dimensions. A general and flexible approach for the construction of nonlinear (morphological) wavelets is provided by the lifting scheme. This paper discusses one example in considerable detail, the max-lifting scheme, which has the intriguing property that it preserves local maxima in a signal over a range of scales, depending on how local or global these maxima are.
GPS positioning in a multipath environment

We address the problem of GPS signal delay estimation in a multipath environment with a low-complexity constraint. After recalling the usual early–late estimator and its bias in a multipath propagation context, we study the maximum-likelihood estimator (MLE) based on a signal model including the parametric contribution of reflected components. It results in an efficient algorithm using the existing architecture, which is also very simple and cheap to implement. Simulations show that the results of the proposed algorithm, in a multipath environment, are similar to these of the early–late in a single-path environment. The performance are further characterized, for both MLEs (based on the single-path and multipath propagation) in terms of bias and standard deviation. The expressions of the corresponding Cramér—Rao (CR) bounds are derived in both cases to show the good performance of the estimators when unbiased.
Toward Supervised Anomaly Detection

Anomaly detection is being regarded as an unsupervised learning task as anomalies stem from adversarial or unlikely events with unknown distributions. However, the predictive performance of purely unsupervised anomaly detection often fails to match the required detection rates in many tasks and there exists a need for labeled data to guide the model generation. Our first contribution shows that classical semi-supervised approaches, originating from a supervised classifier, are inappropriate and hardly detect new and unknown anomalies. We argue that semi-supervised anomaly detection needs to ground on the unsupervised learning paradigm and devise a novel algorithm that meets this requirement. Although being intrinsically non-convex, we further show that the optimization problem has a convex equivalent under relatively mild assumptions. Additionally, we propose an active learning strategy to automatically filter candidates for labeling. In an empirical study on network intrusion detection data, we observe that the proposed learning methodology requires much less labeled data than the state-of-the-art, while achieving higher detection accuracies.
Clonal Evolution in Breast Cancer Revealed by Single Nucleus Genome Sequencing

Sequencing studies of breast tumour cohorts have identified many prevalent mutations, but provide limited insight into the genomic diversity within tumours. Here we developed a whole-genome and exome single cell sequencing approach called nuc-seq that uses G2/M nuclei to achieve 91% mean coverage breadth. We applied this method to sequence single normal and tumour nuclei from an oestrogen-receptor-positive (ER+) breast cancer and a triple-negative ductal carcinoma. In parallel, we performed single nuclei copy number profiling. Our data show that aneuploid rearrangements occurred early in tumour evolution and remained highly stable as the tumour masses clonally expanded. In contrast, point mutations evolved gradually, generating extensive clonal diversity. Using targeted single-molecule sequencing, many of the diverse mutations were shown to occur at low frequencies (<10%) in the tumour mass. Using mathematical modelling we found that the triple-negative tumour cells had an increased mutation rate (13.3×), whereas the ER+ tumour cells did not. These findings have important implications for the diagnosis, therapeutic treatment and evolution of chemoresistance in breast cancer.
Through wall sensing of human breathing and heart beating by monochromatic radar

A radar for detecting and testing health condition of an individual, who is separated from the radar by a non-metal wall or in poor visibility, could be useful in many critical services such as medicine, rescue service, law and antiterrorists enforcements In this paper, we describe the theoretical approach and experiments utilizing a continuous-wave subsurface radar. New theoretical results, experimental records and their frequency spectrums for heartbeat, respiration and articulation of a man are presented.