OpenRaiser/Intern-Atlas huggingface dataset:
A Deterministic Algorithm for Maximizing Submodular Functions
Venue: arXiv cs.DS 2015
Year: 2015

The problem of maximizing a non-negative submodular function was introduced by Feige, Mirrokni, and Vondrak [FOCS'07] who provided a deterministic local-search based algorithm that guarantees an approximation ratio of $\frac 1 3$, as well as a randomized $\frac 2 5$-approximation algorithm. An extensive line of research followed and various algorithms with improving approximation ratios were developed, all of them are randomized. Finally, Buchbinder et al. [FOCS'12] presented a randomized $\frac 1 2$-approximation algorithm, which is the best possible. This paper gives the first deterministic algorithm for maximizing a non-negative submodular function that achieves an approximation ratio better than $\frac 1 3$. The approximation ratio of our algorithm is $\frac 2 5$. Our algorithm is based on recursive composition of solutions obtained by the local search algorithm of Feige et al. We show that the $\frac 2 5$ approximation ratio can be guaranteed when the recursion depth is $2$, and leave open the question of whether the approximation ratio improves as the recursion depth increases.
Improved Opportunistic Sleeping Algorithms for LAN Switches
Venue: arXiv cs.NI 2015
Year: 2015

Network interfaces in most LAN computing devices are usually severely under-utilized, wasting energy while waiting for new packets to arrive. In this paper, we present two algorithms for opportunistically powering down unused network interfaces in order to save some of that wasted energy. We compare our proposals to the best known opportunistic method, and show that they provide much greater power savings inflicting even lower delays to Internet traffic.
Optimizing CMS build infrastructure via Apache Mesos
Venue: arXiv cs.DC 2015
Year: 2015

The Offline Software of the CMS Experiment at the Large Hadron Collider (LHC) at CERN consists of 6M lines of in-house code, developed over a decade by nearly 1000 physicists, as well as a comparable amount of general use open-source code. A critical ingredient to the success of the construction and early operation of the WLCG was the convergence, around the year 2000, on the use of a homogeneous environment of commodity x86-64 processors and Linux. Apache Mesos is a cluster manager that provides efficient resource isolation and sharing across distributed applications, or frameworks. It can run Hadoop, Jenkins, Spark, Aurora, and other applications on a dynamically shared pool of nodes. We present how we migrated our continuos integration system to schedule jobs on a relatively small Apache Mesos enabled cluster and how this resulted in better resource usage, higher peak performance and lower latency thanks to the dynamic scheduling capabilities of Mesos.
Designing Computing System Architecture and Models for the HL-LHC era
Venue: arXiv cs.DC 2015
Year: 2015

This paper describes a programme to study the computing model in CMS after the next long shutdown near the end of the decade.
Testing Consumer Rationality using Perfect Graphs and Oriented Discs
Venue: arXiv cs.CC 2015
Year: 2015

Given a consumer data-set, the axioms of revealed preference proffer a binary test for rational behaviour. A natural (non-binary) measure of the degree of rationality exhibited by the consumer is the minimum number of data points whose removal induces a rationalisable data-set.We study the computational complexity of the resultant consumer rationality problem in this paper. This problem is, in the worst case, equivalent (in terms of approximation) to the directed feedback vertex set problem. Our main result is to obtain an exact threshold on the number of commodities that separates easy cases and hard cases. Specifically, for two-commodity markets the consumer rationality problem is polynomial time solvable; we prove this via a reduction to the vertex cover problem on perfect graphs. For three-commodity markets, however, the problem is NP-complete; we prove thisusing a reduction from planar 3-SAT that is based upon oriented-disc drawings.
Projected Model Counting
Venue: arXiv cs.AI 2015
Year: 2015

Model counting is the task of computing the number of assignments to variables V that satisfy a given propositional theory F. Model counting is an essential tool in probabilistic reasoning. In this paper, we introduce the problem of model counting projected on a subset P of original variables that we call 'priority' variables. The task is to compute the number of assignments to P such that there exists an extension to 'non-priority' variables V¶that satisfies F. Projected model counting arises when some parts of the model are irrelevant to the counts, in particular when we require additional variables to model the problem we are counting in SAT. We discuss three different approaches to projected model counting (two of which are novel), and compare their performance on different benchmark problems. To appear in 18th International Conference on Theory and Applications of Satisfiability Testing, September 24-27, 2015, Austin, Texas, USA
A Hyperelastic Two-Scale Optimization Model for Shape Matching
Venue: arXiv cs.CG 2015
Year: 2015

We suggest a novel shape matching algorithm for three-dimensional surface meshes of disk or sphere topology. The method is based on the physical theory of nonlinear elasticity and can hence handle large rotations and deformations. Deformation boundary conditions that supplement the underlying equations are usually unknown. Given an initial guess, these are optimized such that the mechanical boundary forces that are responsible for the deformation are of a simple nature. We show a heuristic way to approximate the nonlinear optimization problem by a sequence of convex problems using finite elements. The deformation cost, i.e, the forces, is measured on a coarse scale while ICP-like matching is done on the fine scale. We demonstrate the plausibility of our algorithm on examples taken from different datasets.
SynapCountJ --- a Tool for Analyzing Synaptic Densities in Neurons
Venue: arXiv cs.CV 2015
Year: 2015

The quantification of synapses is instrumental to measure the evolution of synaptic densities of neurons under the effect of some physiological conditions, neuronal diseases or even drug treatments. However, the manual quantification of synapses is a tedious, error-prone, time-consuming and subjective task; therefore, tools that might automate this process are desirable. In this paper, we present SynapCountJ, an ImageJ plugin, that can measure synaptic density of individual neurons obtained by immunofluorescence techniques, and also can be applied for batch processing of neurons that have been obtained in the same experiment or using the same setting. The procedure to quantify synapses implemented in SynapCountJ is based on the colocalization of three images of the same neuron (the neuron marked with two antibody markers and the structure of the neuron) and is inspired by methods coming from Computational Algebraic Topology. SynapCountJ provides a procedure to semi-automatically quantify the number of synapses of neuron cultures; as a result, the time required for such an analysis is greatly reduced.
Web Tracking: Mechanisms, Implications, and Defenses
Venue: arXiv cs.CY 2015
Year: 2015

This articles surveys the existing literature on the methods currently used by web services to track the user online as well as their purposes, implications, and possible user's defenses. A significant majority of reviewed articles and web resources are from years 2012-2014. Privacy seems to be the Achilles' heel of today's web. Web services make continuous efforts to obtain as much information as they can about the things we search, the sites we visit, the people with who we contact, and the products we buy. Tracking is usually performed for commercial purposes. We present 5 main groups of methods used for user tracking, which are based on sessions, client storage, client cache, fingerprinting, or yet other approaches. A special focus is placed on mechanisms that use web caches, operational caches, and fingerprinting, as they are usually very rich in terms of using various creative methodologies. We also show how the users can be identified on the web and associated with their real names, e-mail addresses, phone numbers, or even street addresses. We show why tracking is being used and its possible implications for the users (price discrimination, assessing financial credibility, determining insurance coverage, government surveillance, and identity theft). For each of the tracking methods, we present possible defenses. Apart from describing the methods and tools used for keeping the personal data away from being tracked, we also present several tools that were used for research purposes - their main goal is to discover how and by which entity the users are being tracked on their desktop computers or smartphones, provide this information to the users, and visualize it in an accessible and easy to follow way. Finally, we present the currently proposed future approaches to track the user and show that they can potentially pose significant threats to the users' privacy.
The Cost of Free Spectrum
Venue: arXiv cs.GT 2015
Year: 2015

There has been growing interest in increasing the amount of radio spectrum available for unlicensed broad-band wireless access. That includes "prime" spectrum at lower frequencies, which is also suitable for wide area coverage by licensed cellular providers. While additional unlicensed spectrum would allow for market expansion, it could influence competition among providers and increase congestion (interference) among consumers of wireless services. We study the value (social welfare and consumer surplus) obtained by adding unlicensed spectrum to an existing allocation of licensed spectrum among incumbent service providers. We assume a population of customers who choose a provider based on the minimum delivered price, given by the weighted sum of the price of the service and a congestion cost, which depends on the number of subscribers in a band. We consider models in which this weighting is uniform across the customer population and where the weighting is either high or low, reflecting different sensitivities to latency. For the models considered, we find that the social welfare depends on the amount of additional unlicensed spectrum, and can actually decrease over a significant range of unlicensed bandwidths. Furthermore, with nonuniform weighting, introducing unlicensed spectrum can also reduce consumer welfare.
A simple and numerically stable primal-dual algorithm for computing Nash-equilibria in sequential games with incomplete information
Venue: arXiv cs.GT 2015
Year: 2015

We present a simple primal-dual algorithm for computing approximate Nash-equilibria in two-person zero-sum sequential games with incomplete information and perfect recall (like Texas Hold'em Poker). Our algorithm is numerically stable, performs only basic iterations (i.e matvec multiplications, clipping, etc., and no calls to external first-order oracles, no matrix inversions, etc.), and is applicable to a broad class of two-person zero-sum games including simultaneous games and sequential games with incomplete information and perfect recall. The applicability to the latter kind of games is thanks to the sequence-form representation which allows us to encode any such game as a matrix game with convex polytopial strategy profiles. We prove that the number of iterations needed to produce a Nash-equilibrium with a given precision is inversely proportional to the precision. As proof-of-concept, we present experimental results on matrix games on simplexes and Kuhn Poker.
A constrained optimization perspective on actor critic algorithms and application to network routing
Venue: arXiv cs.LG 2015
Year: 2015

We propose a novel actor-critic algorithm with guaranteed convergence to an optimal policy for a discounted reward Markov decision process. The actor incorporates a descent direction that is motivated by the solution of a certain non-linear optimization problem. We also discuss an extension to incorporate function approximation and demonstrate the practicality of our algorithms on a network routing application.
Adapted sampling for 3D X-ray computed tomography
Venue: arXiv cs.CV 2015
Year: 2015

In this paper, we introduce a method to build an adapted mesh representation of a 3D object for X-Ray tomography reconstruction. Using this representation, we provide means to reduce the computational cost of reconstruction by way of iterative algorithms. The adapted sampling of the reconstruction space is directly obtained from the projection dataset and prior to any reconstruction. It is built following two stages : firstly, 2D structural information is extracted from the projection images and is secondly merged in 3D to obtain a 3D pointcloud sampling the interfaces of the object. A relevant mesh is then built from this cloud by way of tetrahedralization. Critical parameters selections have been automatized through a statistical framework, thus avoiding dependence on users expertise. Applying this approach on geometrical shapes and on a 3D Shepp-Logan phantom, we show the relevance of such a sampling - obtained in a few seconds - and the drastic decrease in cells number to be estimated during reconstruction when compared to the usual regular voxel lattice. A first iterative reconstruction of the Shepp-Logan using this kind of sampling shows the relevant advantages in terms of low dose or sparse acquisition sampling contexts. The method can also prove useful for other applications such as finite element method computations.
Collaborative Representation Classification Ensemble for Face Recognition
Venue: arXiv cs.CV 2015
Year: 2015

Collaborative Representation Classification (CRC) for face recognition attracts a lot attention recently due to its good recognition performance and fast speed. Compared to Sparse Representation Classification (SRC), CRC achieves a comparable recognition performance with 10-1000 times faster speed. In this paper, we propose to ensemble several CRC models to promote the recognition rate, where each CRC model uses different and divergent randomly generated biologically-inspired features as the face representation. The proposed ensemble algorithm calculates an ensemble weight for each CRC model that guided by the underlying classification rule of CRC. The obtained weights reflect the confidences of those CRC models where the more confident CRC models have larger weights. The proposed weighted ensemble method proves to be very effective and improves the performance of each CRC model significantly. Extensive experiments are conducted to show the superior performance of the proposed method.
Tracking Randomly Moving Objects on Edge Box Proposals
Venue: arXiv cs.CV 2015
Year: 2015

Most tracking-by-detection methods employ a local search window around the predicted object location in the current frame assuming the previous location is accurate, the trajectory is smooth, and the computational capacity permits a search radius that can accommodate the maximum speed yet small enough to reduce mismatches. These, however, may not be valid always, in particular for fast and irregularly moving objects. Here, we present an object tracker that is not limited to a local search window and has ability to probe efficiently the entire frame. Our method generates a small number of "high-quality" proposals by a novel instance-specific objectness measure and evaluates them against the object model that can be adopted from an existing tracking-by-detection approach as a core tracker. During the tracking process, we update the object model concentrating on hard false-positives supplied by the proposals, which help suppressing distractors caused by difficult background clutters, and learn how to re-rank proposals according to the object model. Since we reduce significantly the number of hypotheses the core tracker evaluates, we can use richer object descriptors and stronger detector. Our method outperforms most recent state-of-the-art trackers on popular tracking benchmarks, and provides improved robustness for fast moving objects as well as for ultra low-frame-rate videos.
Stability and Equilibrium Analysis of Laneless Traffic with Local Control Laws
Venue: arXiv cs.SY 2015
Year: 2015

In this paper, a new model for traffic on roads with multiple lanes is developed, where the vehicles do not adhere to a lane discipline. Assuming identical vehicles, the dynamics is split along two independent directions: the Y-axis representing the direction of motion and the X-axis representing the lateral or the direction perpendicular to the direction of motion. Different influence graphs are used to model the interaction between the vehicles in these two directions. The instantaneous accelerations of each car, in both X and Y directions, are functions of the measurements from the neighbouring cars according to these influence graphs. The stability and equilibrium spacings of the car formation is analyzed for usual traffic situations such as steady flow, obstacles, lane changing and rogue drivers arbitrarily changing positions inside the formation. Conditions are derived under which the formation maintains stability and the desired intercar spacing for each of these traffic events. Simulations for some of these scenarios are included.
Extending PPTL for Verifying Heap Evolution Properties
Venue: arXiv cs.LO 2015
Year: 2015

In this paper, we integrate separation logic with Propositional Projection Temporal Logic (PPTL) to obtain a two-dimensional logic, namely PPTL$^{\tiny\mbox{SL}}$. The spatial dimension is realized by a decidable fragment of separation logic which can be used to describe linked lists, and the temporal dimension is expressed by PPTL. We show that PPTL and PPTL$^{\tiny\mbox{SL}}$ are closely related in their syntax structures. That is, for any PPTL$^{\tiny\mbox{SL}}$ formula in a restricted form, there exists an "isomorphic" PPTL formula. The "isomorphic" PPTL formulas can be obtained by first an equisatisfiable translation and then an isomorphic mapping. As a result, existing theory of PPTL, such as decision procedure for satisfiability and model checking algorithm, can be reused for PPTL$^{\tiny\mbox{SL}}$.
Metadata Embeddings for User and Item Cold-start Recommendations
Venue: arXiv cs.IR 2015
Year: 2015

I present a hybrid matrix factorisation model representing users and items as linear combinations of their content features' latent factors. The model outperforms both collaborative and content-based models in cold-start or sparse interaction data scenarios (using both user and item metadata), and performs at least as well as a pure collaborative matrix factorisation model where interaction data is abundant. Additionally, feature embeddings produced by the model encode semantic information in a way reminiscent of word embedding approaches, making them useful for a range of related tasks such as tag recommendations.
aDTN - Undetectable Communication in Wireless Delay-tolerant Networks (Working Draft)
Venue: arXiv cs.CR 2015
Year: 2015

This document describes a best-effort delay-tolerant communication system that protects the privacy of users in wireless ad-hoc networks by making their communication undetectable. The proposed system is a wireless broadcast-based adaptation of mix networks where each user belongs to at least one group it trusts, and each group acts as a mix node. Assuming encryption is not broken, it provides undetectability of all users and messages against external adversaries, as well as undetectability of users and messages in non-compromised groups against internal adversaries.
About embedded quarters and points at infinity in the hyperbolic plane
Venue: arXiv cs.CG 2015
Year: 2015

In this paper, we prove two results. First, there is a family of sequences of embedded quarters of the hyperbolic plane such that any sequence converges to a limit which is an end of the hyperbolic plane. Second, there is no algorithm which would allow us to check whether two given ends are equal or not.
Diffusion Adaptation Over Clustered Multitask Networks Based on the Affine Projection Algorithm
Venue: arXiv cs.DC 2015
Year: 2015

Distributed adaptive networks achieve better estimation performance by exploiting temporal and as well spatial diversity while consuming few resources. Recent works have studied the single task distributed estimation problem, in which the nodes estimate a single optimum parameter vector collaboratively. However, there are many important applications where the multiple vectors have to estimated simultaneously, in a collaborative manner. This paper presents multi-task diffusion strategies based on the Affine Projection Algorithm (APA), usage of APA makes the algorithm robust against the correlated input. The performance analysis of the proposed multi-task diffusion APA algorithm is studied in mean and mean square sense. And also a modified multi-task diffusion strategy is proposed that improves the performance in terms of convergence rate and steady state EMSE as well. Simulations are conducted to verify the analytical results.
Agglomerative clustering and collectiveness measure via exponent generating function
Venue: arXiv cs.CV 2015
Year: 2015

The key in agglomerative clustering is to define the affinity measure between two sets. A novel agglomerative clustering method is proposed by utilizing the path integral to define the affinity measure. Firstly, the path integral descriptor of an edge, a node and a set is computed by path integral and exponent generating function. Then, the affinity measure between two sets is obtained by path integral descriptor of sets. Several good properties of the path integral descriptor is proposed in this paper. In addition, we give the physical interpretation of the proposed path integral descriptor of a set. The proposed path integral descriptor of a set can be regard as the collectiveness measure of a set, which can be a moving system such as human crowd, sheep herd and so on. Self-driven particle (SDP) model is used to test the ability of the proposed method in measuring collectiveness.
Fast, Flexible, and Declarative Construction of Abstract Syntax Trees with PEGs
Venue: arXiv cs.PL 2015
Year: 2015

We address a declarative construction of abstract syntax trees with Parsing Expression Grammars. AST operators (constructor, connector, and tagging) are newly defined to specify flexible AST constructions. A new challenge coming with PEGs is the consistency management of ASTs in backtracking and packrat parsing. We make the transaction AST machine in order to perform AST operations in the context of the speculative parsing of PEGs. All the consistency control is automated by the analysis of AST operators. The proposed approach is implemented in the Nez parser, written in Java. The performance study shows that the transactional AST machine requires 25\% approximately more time in CSV, XML, and C grammars.
Block Iterative Reweighted Algorithms for Super-Resolution of Spectrally Sparse Signals
Venue: arXiv cs.IT 2015
Year: 2015

We propose novel algorithms that enhance the performance of recovering unknown continuous-valued frequencies from undersampled signals. Our iterative reweighted frequency recovery algorithms employ the support knowledge gained from earlier steps of our algorithms as block prior information to enhance frequency recovery. Our methods improve the performance of the atomic norm minimization which is a useful heuristic in recovering continuous-valued frequency contents. Numerical results demonstrate that our block iterative reweighted methods provide both better recovery performance and faster speed than other known methods.