nils-herrmann/clean_scirepeval huggingface dataset:
Retargeting Without Tracking

Retargeting ads are increasingly prevalent on the Internet as their effectiveness has been shown to outperform conventional targeted ads. Retargeting ads are not only based on users' interests, but also on their intents, i.e. commercial products users have shown interest in. Existing retargeting systems heavily rely on tracking, as retargeting companies need to know not only the websites a user has visited but also the exact products on these sites. They are therefore very intrusive, and privacy threatening. Furthermore, these schemes are still sub-optimal since tracking is partial, and they often deliver ads that are obsolete (because, for example, the targeted user has already bought the advertised product). 
This paper presents the first privacy-preserving retargeting ads system. In the proposed scheme, the retargeting algorithm is distributed between the user and the advertiser such that no systematic tracking is necessary, more control and transparency is provided to users, but still a lot of targeting flexibility is provided to advertisers. We show that our scheme, that relies on homomorphic encryption, can be efficiently implemented and trivially solves many problems of existing schemes, such as frequency capping and ads freshness.
Collective computation in a network with distributed information

We analyze a distributed information network in which each node has access to the information contained in a limited set of nodes (its neighborhood) at a given time. A collective computation is carried out in which each node calculates a value that implies all information contained in the network (in our case, the average value of a variable that can take different values in each network node). The neighborhoods can change dynamically by exchanging neighbors with other nodes. The results of this collective calculation show rapid convergence and good scalability with the network size. These results are compared with those of a fixed network arranged as a square lattice, in which the number of rounds to achieve a given accuracy is very high when the size of the network increases. The results for the evolving networks are interpreted in light of the properties of complex networks and are directly relevant to the diameter and characteristic path length of the networks, which seem to express "small world" properties.
A new space for comparing graphs

Finding a new mathematical representation for graphs, which allows direct comparison between different graph structures, is an open-ended research direction. Having such a representation is the first prerequisite for a variety of machine learning algorithms like classification, clustering, etc., over graph datasets. In this paper, we propose a symmetric positive semidefinite matrix with the (i, j)-th entry equal to the covariance between normalized vectors Aie and Aje (e being vector of all ones) as a representation for a graph with adjacency matrix A. We show that the proposed matrix representation encodes the spectrum of the underlying adjacency matrix and it also contains information about the counts of small sub-structures present in the graph such as triangles and small paths. In addition, we show that this matrix is a “graph invariant”. All these properties make the proposed matrix a suitable object for representing graphs. The representation, being a covariance matrix in a fixed dimensional metric space, gives a mathematical embedding for graphs. This naturally leads to a measure of similarity on graph objects. We define similarity between two given graphs as a Bhattacharya similarity measure between their corresponding covariance matrix representations. As shown in our experimental study on the task of social network classification, such a similarity measure outperforms other widely used state-of-the-art methodologies. Our proposed method is also computationally efficient. The computation of both the matrix representation and the similarity value can be performed in operations linear in the number of edges. This makes our method scalable in practice. We believe our theoretical and empirical results provide evidence for studying truncated power iterations, of the adjacency matrix, to characterize social networks.
Hierarchical Quasi-Clustering Methods for Asymmetric Networks

This paper introduces hierarchical quasi-clustering methods, a generalization of hierarchical clustering for asymmetric networks where the output structure preserves the asymmetry of the input data. We show that this output structure is equivalent to a finite quasi-ultrametric space and study admissibility with respect to two desirable properties. We prove that a modified version of single linkage is the only admissible quasi-clustering method. Moreover, we show stability of the proposed method and we establish invariance properties fulfilled by it. Algorithms are further developed and the value of quasi-clustering analysis is illustrated with a study of internal migration within United States.
Approximation for the Path Complexity of Binary Search Tree

The complexity of an algorithm is an important parameter to determine its effi-ciency. They are of different types viz. Time complexity, Space complexity, etc. However, none of them consider the execution path as a complexity measure. Ashok et al, firstly proposed the notion of the Path Complexity of a pro-gram/algorithm, which defined based on the number of execution paths as a function of the input size. However, the notion of path complexity of the pro-gram, cannot apply to the object-oriented environment. Therefore, Anupam et al, has extended the notion of path complexity to the class as follows. The notion of the state of the class is defined based on structural representation (aka state) of the class. The class contains data members and data operations. It considers only those data operations that change the state of the class. The path complexity of the class is defined to be the number of valid input sequences, each of them con-taining valid data operations. Anupam et al, had applied this notion to the class Stack. However, the stack is basic and simple data structures. Therefore, in this research we have used a more complex class to understand the path complexity behavior in the object oriented environment. Binary Search Tree (BST) is one of the well known (and more complex too) data structure, which is useful in sorting, searching, Traffic Engineering and many more applications. We have analyzed the path complexity of the class BST based on the algorithms for insert and delete operations. Additionally, we have modified the delete operation to minimize the path complexity for the class BST.
Promoting Cold-Start Items in Recommender Systems

As one of the major challenges, cold-start problem plagues nearly all recommender systems. In particular, new items will be overlooked, impeding the development of new products online. Given limited resources, how to utilize the knowledge of recommender systems and design efficient marketing strategy for new items is extremely important. In this paper, we convert this ticklish issue into a clear mathematical problem based on a bipartite network representation. Under the most widely used algorithm in real e-commerce recommender systems, the so-called item-based collaborative filtering, we show that to simply push new items to active users is not a good strategy. Interestingly, experiments on real recommender systems indicate that to connect new items with some less active users will statistically yield better performance, namely, these new items will have more chance to appear in other users' recommendation lists. Further analysis suggests that the disassortative nature of recommender systems contributes to such observation. In a word, getting in-depth understanding on recommender systems could pave the way for the owners to popularize their cold-start products with low costs.
Oklo reactors and implications for nuclear science

We summarize the nuclear physics interests in the Oklo natural nuclear reactors, focusing particularly on developments over the past two decades. Modeling of the reactors has become increasingly sophisticated, employing Monte Carlo simulations with realistic geometries and materials that can generate both the thermal and epithermal fractions. The water content and the temperatures of the reactors have been uncertain parameters. We discuss recent work pointing to lower temperatures than earlier assumed. Nuclear cross-sections are input to all Oklo modeling and we discuss a parameter, the 175Lu ground state cross-section for thermal neutron capture leading to the isomer 176mLu, that warrants further investigation. Studies of the time dependence of dimensionless fundamental constants have been a driver for much of the recent work on Oklo. We critically review neutron resonance energy shifts and their dependence on the fine structure constant α and the ratio Xq = mq/Λ (where mq is the average of the u and d current quark masses and Λ is the mass scale of quantum chromodynamics (QCD)). We suggest a formula for the combined sensitivity to α and Xq that exhibits the dependence on proton number Z and mass number A, potentially allowing quantum electrodynamic (QED) and QCD effects to be disentangled if a broader range of isotopic abundance data becomes available.
Tight Bounds for Learning a Mixture of Two Gaussians

We consider the problem of identifying the parameters of an unknown mixture of two arbitrary d-dimensional gaussians from a sequence of independent random samples. Our main results are upper and lower bounds giving a computationally efficient moment-based estimator with an optimal convergence rate, thus resolving a problem introduced by Pearson (1894). Denoting by σ2 the variance of the unknown mixture, we prove that Θ(σ12) samples are necessary and sufficient to estimate each parameter up to constant additive error when d=1. Our upper bound extends to arbitrary dimension d>1 up to a (provably necessary) logarithmic loss in d using a novel---yet simple---dimensionality reduction technique. We further identify several interesting special cases where the sample complexity is notably smaller than our optimal worst-case bound. For instance, if the means of the two components are separated by Ω(σ) the sample complexity reduces to O(σ2) and this is again optimal. Our results also apply to learning each component of the mixture up to small error in total variation distance, where our algorithm gives strong improvements in sample complexity over previous work.
Mapping to a Reference Genome Structure

To support comparative genomics, population genetics, and medical genetics, we propose that a reference genome should come with a scheme for mapping each base in any DNA string to a position in that reference genome. We refer to a collection of one or more reference genomes and a scheme for mapping to their positions as a reference structure. Here we describe the desirable properties of reference structures and give examples. To account for natural genetic variation, we consider the more general case in which a reference genome is represented by a graph rather than a set of phased chromosomes; the latter is treated as a special case.
Critical behavior of charged Gauss-Bonnet-AdS black holes in the grand canonical ensemble

We study the thermodynamics in the grand canonical ensemble of $D$-dimensional charged Gauss-Bonnet-AdS black holes in the extended phase space. We find that the usual small-large black hole phase transition, which exhibits analogy with the van der Waals liquid-gas system, holds in five-dimensional spherical charged Gauss-Bonnet-AdS black holes when its potential is fixed within the range $0l\mathrm{\ensuremath{\Phi}}l\frac{\sqrt{3}\ensuremath{\pi}}{4}$. For the other higher dimensional and topological charged Gauss-Bonnet-AdS black holes, there is no such phase transition. In the limiting case, Reissner-Nordstrom AdS black holes, with vanishing Gauss-Bonnet parameter, there is no critical behavior in the grand canonical ensemble. This result holds independent of the spacetime dimensions and topologies. We also examine the behavior of physical quantities in the vicinity of the critical point in the five-dimensional spherical charged Gauss-Bonnet-AdS black holes.
Discretization independence implies non-locality in 4D discrete quantum gravity

The 4D Regge action is invariant under 5–1 and 4–2 Pachner moves, which define a subset of (local) changes of the triangulation. Given this fact, one might hope to find a local path integral measure that makes the quantum theory invariant under these moves and hence makes the theory partially triangulation invariant. We show that such a local invariant path integral measure does not exist for the 4D linearized Regge theory. To this end we uncover an interesting geometric interpretation for the Hessian of the 4D Regge action. This geometric interpretation will allow us to prove that the determinant of the Hessian of the 4D Regge action does not factorize over four-simplices or subsimplices. It furthermore allows us to determine configurations where this Hessian vanishes, which only appears to be the case in degenerate backgrounds or if one allows for different orientations of the simplices. We suggest a non-local measure factor that absorbs the non-local part of the determinant of the Hessian under 5–1 moves as well as a local measure factor that is preserved for very special configurations.
Critique of J. Kim's "P is not equal to NP by Modus Tollens"

This paper is a critique of version three of Joonmo Kim's paper entitled "P is not equal to NP by Modus Tollens. " After summarizing Kim's proof, we note that the logic that Kim uses is inconsistent, which provides evidence that the proof is invalid. To show this, we will consider two reasonable interpretations of Kim's definitions, and show that "P is not equal to NP" does not seem to follow in an obvious way using any of them.
Linking geographic vocabularies through WordNet

The linked open data (LOD) paradigm has emerged as a promising approach to structuring and sharing geospatial information. One of the major obstacles to this vision lies in the difficulties found in the automatic integration between heterogeneous vocabularies and ontologies that provides the semantic backbone of the growing constellation of open geo-knowledge bases. In this article, we show how to utilize WordNet as a semantic hub to increase the integration of LOD. With this purpose in mind, we devise Voc2WordNet, an unsupervised mapping technique between a given vocabulary and WordNet, combining intensional and extensional aspects of the geographic terms. Voc2WordNet is evaluated against a sample of human-generated alignments with the OpenStreetMap (OSM) Semantic Network, a crowdsourced geospatial resource, and the GeoNames ontology, the vocabulary of a large digital gazetteer. These empirical results indicate that the approach can obtain high precision and recall.
Cooperating distributed context-free hexagonal array grammar systems with permitting contexts

In this paper we associate permitting symbols with rules of Grammars in the components of cooperating distributed context free hexagonal array grammar systems as a control mechanism and investigating the generative power of the resulting systems in the terminal mode. This feature of associating permitting symbols with rules when extended to patterns in the form of connected arrays also requires checking of symbols, but this is simpler than usual pattern matching. The benefit of allowing permitting symbols is that it enables us to reduce the number of components required in a cooperating distributed hexagonal array grammar system for generating a set of picture arrays.
Estimating binding properties of transcription factors from genome-wide binding profiles

The binding of transcription factors (TFs) is essential for gene expression. One important characteristic is the actual occupancy of a putative binding site in the genome. In this study, we propose an analytical model to predict genomic occupancy that incorporates the preferred target sequence of a TF in the form of a position weight matrix (PWM), DNA accessibility data (in the case of eukaryotes), the number of TF molecules expected to be bound specifically to the DNA and a parameter that modulates the specificity of the TF. Given actual occupancy data in the form of ChIP-seq profiles, we backwards inferred copy number and specificity for five Drosophila TFs during early embryonic development: Bicoid, Caudal, Giant, Hunchback and Kruppel. Our results suggest that these TFs display thousands of molecules that are specifically bound to the DNA and that whilst Bicoid and Caudal display a higher specificity, the other three TFs (Giant, Hunchback and Kruppel) display lower specificity in their binding (despite having PWMs with higher information content). This study gives further weight to earlier investigations into TF copy numbers that suggest a significant proportion of molecules are not bound specifically to the DNA.
IMP Science Gateway: From the Portal to the Hub of Virtual Experimental Labs in Materials Science

Science gateway (SG) ideology means a user-friendly intuitive interface between scientists (or scientific communities) and different software components + various distributed computing infrastructures (DCIs) (like grids, clouds, clusters), where researchers can focus on their scientific goals and less on peculiarities of software/DCI. "IMP Science Gateway Portal" (http://scigate.imp.kiev.ua) for complex workflow management and integration of distributed computing resources (like clusters, service grids, desktop grids, clouds) is presented. It is created on the basis of WS-PGRADE and gUSE technologies, where WS-PGRADE is designed for science workflow operation and gUSE - for smooth integration of available resources for parallel and distributed computing in various heterogeneous distributed computing infrastructures (DCI). The typical scientific workflows with possible scenarios of its preparation and usage are presented. Several typical use cases for these science applications (scientific workflows) are considered for molecular dynamics (MD) simulations of complex behavior of various nanostructures (nanoindentation of graphene layers, defect system relaxation in metal nanocrystals, thermal stability of boron nitride nanotubes, etc.). The user experience is analyzed in the context of its practical applications for MD simulations in materials science, physics and nanotechnologies with available heterogeneous DCIs. In conclusion, the "science gateway" approach - workflow manager (like WS-PGRADE) + DCI resources manager (like gUSE)-gives opportunity to use the SG portal (like "IMP Science Gateway Portal") in a very promising way, namely, as a hub of various virtual experimental labs (different software components + various requirements to resources) in the context of practical MD applications in materials science, physics, and nanotechnologies.
On the abundance of circumbinary planets

Circumbinary planets are bodies that orbit both components in a binary star system. This thesis focuses on transits of these planets, which with the aid of the Kepler space telescope have recently led to the discovery of several such objects. First, transit timing variations - departures from strict periodicity in the transit times - are studied. These arise from both the motion of the host stars and relatively rapid precession of the planet’s orbit. Limits on the maximum possible transit timing variation are derived, and tested against N-body simulations of simulated circumbinary systems. 
 
These limits are then utilised to form a search algorithm designed to find these planets in light curves, focusing on data from the WASP and Kepler observatories. This search algorithm uses an individual transit search to identify potential transit signatures, then forms periodograms allowing for the possible timing variations. It is used to identify several new candidate planets, as well as confirm detections of previously known circumbinary systems. In addition a number of interesting multiple stellar systems are identified including the as yet unexplained KIC2856960, which display multiple eclipses, significant tidal heating or rapid orbital evolution on the timescale of the 4 year Kepler observations. 
 
In 2013 unbiased stellar radii for the eclipsing binaries of the Kepler dataset were not available. A catalogue is produced, derived from spectral energy distribution fits to data from the KIS, HES and 2MASS surveys of the Kepler field, which gives temperatures for these stars accurate to⇠300K. These are then used to find calibrated stellar masses and radii. These parameters, in combination with the search algorithm, are used to study circumbinary planet rates of occurrence in the Kepler dataset. The known sample of eclipsing binaries is tested for detectability, and a Monte Carlo population synthesis used to find probability density functions for these rates. These are a function of the as yet unknown circumbinary planetary inclination distribution, and show that the rate of occurrence of circumbinary planets is consistent with that of single stars if these planets are in the majority coplanar with their host binaries. However, if they are more misaligned, to a degree greater than that implied by a 5# Gaussian distribution, their rate of occurrence becomes significantly higher. Furthermore, it is confirmed that planets of Jupiter size and greater occur less often in circumbinary configurations, and that circumbinary planets are preferentially found around binaries with periods longer than⇠7 days.
Particle detectors and the zero mode of a quantum field

We study the impact of the zero-mode of a quantum field on the evolution of a particle detector. For a massless scalar field in a periodic cavity, we show that the impact of the zero mode on the Unruh-DeWitt detector and its derivative-coupling generalisation is necessarily nonvanishing but can be made negligible in some limits, including those commonly occurring in non-relativistic quantum optics. For the derivative-coupling detector this can be accomplished by just tuning the zero mode's initial state, but the standard Unruh-DeWitt detector requires a more subtle and careful tuning. Applications include an inertial detector with arbitrary velocity, where we demonstrate the regularity of the ultrarelativistic limit, and a detector with uniform acceleration.
THE FIRST TWO YEARS OF ELECTROMAGNETIC FOLLOW-UP WITH ADVANCED LIGO AND VIRGO

We anticipate the first direct detections of gravitational waves (GWs) with Advanced LIGO and Virgo later this decade. Though this groundbreaking technical achievement will be its own reward, a still greater prize could be observations of compact binary mergers in both gravitational and electromagnetic channels simultaneously. During Advanced LIGO and Virgo's first two years of operation, 2015 through 2016, we expect the global GW detector array to improve in sensitivity and livetime and expand from two to three detectors. We model the detection rate and the sky localization accuracy for binary neutron star (BNS) mergers across this transition. We have analyzed a large, astrophysically motivated source population using real-time detection and sky localization codes and higher-latency parameter estimation codes that have been expressly built for operation in the Advanced LIGO/Virgo era. We show that for most BNS events, the rapid sky localization, available about a minute after a detection, is as accurate as the full parameter estimation. We demonstrate that Advanced Virgo will play an important role in sky localization, even though it is anticipated to come online with only one-third as much sensitivity as the Advanced LIGO detectors. We find that the median 90% confidence region shrinks from ∼500 deg2 in 2015 to ∼200 deg2 in 2016. A few distinct scenarios for the first LIGO/Virgo detections emerge from our simulations.