OpenRaiser/Intern-Atlas huggingface dataset:
The DoF of the Asymmetric MIMO Interference Channel with Square Direct Link Channel Matrices
Venue: arXiv cs.IT 2014
Year: 2014

This paper studies the sum Degrees of Freedom (DoF) of $K$-user {\em asymmetric} MIMO Interference Channel (IC) with square direct link channel matrices, that is, the $u$-th transmitter and its intended receiver have $M_u\in\mathbb{N}$ antennas each, where $M_u$ need not be the same for all $u\in[1:K]$. Starting from a $3$-user example, it is shown that existing cooperation-based outer bounds are insufficient to characterize the DoF. Moreover, it is shown that two distinct operating regimes exist. With a {\it dominant} user, i.e., a user that has more antennas than the other two users combined, %(say $M_1\geq M_2+M_3$), it is DoF optimal to let that user transmit alone on the IC. Otherwise, it is DoF optimal to {\em decompose} and operate the 3-user MIMO IC as an $(M_1+ M_2+M_3)$-user SISO IC. This indicates that MIMO operations are useless from a DoF perspective in systems without a dominant user. The main contribution of the paper is the derivation of a novel outer bound for the general $K$-user case that is tight in the regime where a dominant user is not present; this is done by generalizing the insights from the 3-user example to an arbitrary number of users.
Supervised mid-level features for word image representation
Venue: arXiv cs.CV 2014
Year: 2014

This paper addresses the problem of learning word image representations: given the cropped image of a word, we are interested in finding a descriptive, robust, and compact fixed-length representation. Machine learning techniques can then be supplied with these representations to produce models useful for word retrieval or recognition tasks. Although many works have focused on the machine learning aspect once a global representation has been produced, little work has been devoted to the construction of those base image representations: most works use standard coding and aggregation techniques directly on top of standard computer vision features such as SIFT or HOG. We propose to learn local mid-level features suitable for building word image representations. These features are learnt by leveraging character bounding box annotations on a small set of training images. However, contrary to other approaches that use character bounding box information, our approach does not rely on detecting the individual characters explicitly at testing time. Our local mid-level features can then be aggregated to produce a global word image signature. When pairing these features with the recent word attributes framework of Almazán et al., we obtain results comparable with or better than the state-of-the-art on matching and recognition tasks using global descriptors of only 96 dimensions.
Rearrangement Problems with Duplicated Genomic Markers
Venue: arXiv cs.DS 2014
Year: 2014

Understanding the dynamics of genome rearrangements is a major issue of phylogenetics. Phylogenetics is the study of species evolution. A major goal of the field is to establish evolutionary relationships within groups of species, in order to infer the topology of an evolutionary tree formed by this group and common ancestors to some of these species. In this context, having means to evaluate relative evolutionary distances between species, or to infer common ancestor genomes to a group of species would be of great help. This work, in the vein of other studies from the past, aims at designing such means, here in the particular case where genomes present multiple occurrencies of genes, which makes things more complex. Several hypotheses accounting for the presence of duplications were considered. Distances formulae as well as scenario computing algorithms were established, along with their complexity proofs.
A stronger null hypothesis for crossing dependencies
Venue: arXiv cs.CL 2014
Year: 2014

The syntactic structure of a sentence can be modeled as a tree where vertices are words and edges indicate syntactic dependencies between words. It is well-known that those edges normally do not cross when drawn over the sentence. Here a new null hypothesis for the number of edge crossings of a sentence is presented. That null hypothesis takes into account the length of the pair of edges that may cross and predicts the relative number of crossings in random trees with a small error, suggesting that a ban of crossings or a principle of minimization of crossings are not needed in general to explain the origins of non-crossing dependencies. Our work paves the way for more powerful null hypotheses to investigate the origins of non-crossing dependencies in nature.
Mobility Enhancement for Elderly
Venue: arXiv cs.CV 2014
Year: 2014

Loss of Mobility is a common handicap to senior citizens. It denies them the ease of movement they would like to have like outdoor visits, movement in hospitals, social outgoings, but more seriously in the day to day in-house routine functions necessary for living etc. Trying to overcome this handicap by means of servant or domestic help and simple wheel chairs is not only costly in the long run, but forces the senior citizen to be at the mercy of sincerity of domestic helps and also the consequent loss of dignity. In order to give a dignified life, the mobility obtained must be at the complete discretion, will and control of the senior citizen. This can be provided only by a reasonably sophisticated and versatile wheel chair, giving enhanced ability of vision, hearing through man-machine interface, and sensor aided navigation and control. More often than not senior people have poor vision which makes it difficult for them to maker visual judgement and so calls for the use of Artificial Intelligence in visual image analysis and guided navigation systems. In this project, we deal with two important enhancement features for mobility enhancement, Audio command and Vision aided obstacle detection and navigation. We have implemented speech recognition algorithm using template of stored words for identifying the voice command given by the user. This frees the user of an agile hand to operate joystick or mouse control. Also, we have developed a new appearance based obstacle detection system using stereo-vision cameras which estimates the distance of nearest obstacle to the wheel chair and takes necessary action. This helps user in making better judgement of route and navigate obstacles. The main challenge in this project is how to navigate in an unknown/unfamiliar environment by avoiding obstacles.
Proving Safety with Trace Automata and Bounded Model Checking
Venue: arXiv cs.FL 2014
Year: 2014

Loop under-approximation is a technique that enriches C programs with additional branches that represent the effect of a (limited) range of loop iterations. While this technique can speed up the detection of bugs significantly, it introduces redundant execution traces which may complicate the verification of the program. This holds particularly true for verification tools based on Bounded Model Checking, which incorporate simplistic heuristics to determine whether all feasible iterations of a loop have been considered. We present a technique that uses \emph{trace automata} to eliminate redundant executions after performing loop acceleration. The method reduces the diameter of the program under analysis, which is in certain cases sufficient to allow a safety proof using Bounded Model Checking. Our transformation is precise---it does not introduce false positives, nor does it mask any errors. We have implemented the analysis as a source-to-source transformation, and present experimental results showing the applicability of the technique.
Optimization-based smoothing algorithm for triangle meshes over arbitrarily shaped domains
Venue: arXiv cs.NA 2014
Year: 2014

This paper describes a node relocation algorithm based on nonlinear optimization which delivers excellent results for both unstructured and structured plane triangle meshes over convex as well as non-convex domains with high curvature. The local optimization scheme is a damped Newton's method in which the gradient and Hessian of the objective function are evaluated exactly. The algorithm has been developed in order to continuously rezone the mesh in arbitrary Lagrangian-Eulerian (ALE) methods for large deformation penetration problems, but it is also suitable for initial mesh improvement. Numerical examples highlight the capabilities of the algorithm.
Discovering Organizational Correlations from Twitter
Venue: arXiv cs.SI 2014
Year: 2014

Organizational relationships are usually very complex in real life. It is difficult or impossible to directly measure such correlations among different organizations, because important information is usually not publicly available (e.g., the correlations of terrorist organizations). Nowadays, an increasing amount of organizational information can be posted online by individuals and spread instantly through Twitter. Such information can be crucial for detecting organizational correlations. In this paper, we study the problem of discovering correlations among organizations from Twitter. Mining organizational correlations is a very challenging task due to the following reasons: a) Data in Twitter occurs as large volumes of mixed information. The most relevant information about organizations is often buried. Thus, the organizational correlations can be scattered in multiple places, represented by different forms; b) Making use of information from Twitter collectively and judiciously is difficult because of the multiple representations of organizational correlations that are extracted. In order to address these issues, we propose multi-CG (multiple Correlation Graphs based model), an unsupervised framework that can learn a consensus of correlations among organizations based on multiple representations extracted from Twitter, which is more accurate and robust than correlations based on a single representation. Empirical study shows that the consensus graph extracted from Twitter can capture the organizational correlations effectively.
A Risk Minimization Framework for Channel Estimation in OFDM Systems
Venue: arXiv cs.IT 2014
Year: 2014

We address the problem of channel estimation for cyclic-prefix (CP) Orthogonal Frequency Division Multiplexing (OFDM) systems. We model the channel as a vector of unknown deterministic constants and hence, do not require prior knowledge of the channel statistics. Since the mean-square error (MSE) is not computable in practice, in such a scenario, we propose a novel technique using Stein's lemma to obtain an unbiased estimate of the mean-square error, namely the Stein's unbiased risk estimate (SURE). We obtain an estimate of the channel from noisy observations using linear and nonlinear denoising functions, whose parameters are chosen to minimize SURE. Based on computer simulations, we show that using SURE-based channel estimate in equalization offers an improvement in signal-to-noise ratio of around 2.25 dB over the maximum-likelihood channel estimate, in practical channel scenarios, without assuming prior knowledge of channel statistics.
Computing the Skorokhod Distance between Polygonal Traces (Full Paper)
Venue: arXiv cs.SY 2014
Year: 2014

The \emph{Skorokhod distance} is a natural metric on traces of continuous and hybrid systems. For two traces, from $[0,T]$ to values in a metric space $O$, it measures the best match between the traces when allowed continuous bijective timing distortions. Formally, it computes the infimum, over all timing distortions, of the maximum of two components: the first component quantifies the {\em timing discrepancy} of the timing distortion, and the second quantifies the mismatch (in the metric space $O$) of the values under the timing distortion. Skorokhod distances appear in various fundamental hybrid systems analysis concerns: from definitions of hybrid systems semantics and notions of equivalence, to practical problems such as checking the closeness of models or the quality of simulations. Despite its popularity and extensive theoretical use, the \emph{computation} problem for the Skorokhod distance between two finite sampled-time hybrid traces has remained open. We address in this work the problem of computing the Skorokhod distance between two polygonal traces (these traces arise when sampled-time traces are completed by linear interpolation between sample points). We provide the first algorithm to compute the exact Skorokhod distance when trace values are in $\reals^n$ for the $L_1$, $L_2$, and $L_{\infty}$ norms. Our algorithm, based on a reduction to Frechet distances, is fully polynomial-time, and incorporates novel polynomial-time procedures for a set of geometric primitives in $\reals^n$ over the three norms.
A type assignment for lambda-calculus complete both for FPTIME and strong normalization
Venue: arXiv cs.LO 2014
Year: 2014

One of the aims of Implicit Computational Complexity is the design of programming languages with bounded computational complexity; indeed, guaranteeing and certifying a limited resources usage is of central importance for various aspects of computer science. One of the more promising approaches to this aim is based on the use of lambda-calculus as paradigmatic programming language and the design of type assignment systems for lambda-terms, where types guarantee both the functional correctness and the complexity bound. Here we propose a system of stratified types, inspired by intersection types, where intersection is a non-associative operator. The system, called STR, is correct and complete for polynomial time computations; moreover, all the strongly normalizing terms are typed in it, thus increasing the typing power with respect to the previous proposals. Moreover, STR enjoys a stronger expressivity with respect to the previous system STA, since it allows to type a restricted version of iteration.
Attribute Efficient Linear Regression with Data-Dependent Sampling
Venue: arXiv cs.LG 2014
Year: 2014

In this paper we analyze a budgeted learning setting, in which the learner can only choose and observe a small subset of the attributes of each training example. We develop efficient algorithms for ridge and lasso linear regression, which utilize the geometry of the data by a novel data-dependent sampling scheme. When the learner has prior knowledge on the second moments of the attributes, the optimal sampling probabilities can be calculated precisely, and result in data-dependent improvements factors for the excess risk over the state-of-the-art that may be as large as $O(\sqrt{d})$, where $d$ is the problem's dimension. Moreover, under reasonable assumptions our algorithms can use less attributes than full-information algorithms, which is the main concern in budgeted learning settings. To the best of our knowledge, these are the first algorithms able to do so in our setting. Where no such prior knowledge is available, we develop a simple estimation technique that given a sufficient amount of training examples, achieves similar improvements. We complement our theoretical analysis with experiments on several data sets which support our claims.
Justifying the small-world phenomenon via random recursive trees
Venue: arXiv cs.DM 2014
Year: 2014

We present a new technique for proving logarithmic upper bounds for diameters of evolving random graph models, which is based on defining a coupling between random graphs and variants of random recursive trees. The advantage of the technique is three-fold: it is quite simple and provides short proofs, it is applicable to a broad variety of models including those incorporating preferential attachment, and it provides bounds with small constants. We illustrate this by proving, for the first time, logarithmic upper bounds for the diameters of the following well known models: the forest fire model, the copying model, the PageRank-based selection model, the Aiello-Chung-Lu models, the generalized linear preference model, directed scale-free graphs, the Cooper-Frieze model, and random unordered increasing $k$-trees. Our results shed light on why the small-world phenomenon is observed in so many real-world graphs.
Decidability of the Clark's Completion Semantics for Monadic Programs and Queries
Venue: arXiv cs.LO 2014
Year: 2014

There are many different semantics for general logic programs (i.e. programs that use negation in the bodies of clauses). Most of these semantics are Turing complete (in a sense that can be made precise), implying that they are undecidable. To obtain decidability one needs to put additional restrictions on programs and queries. In logic programming it is natural to put restrictions on the underlying first-order language. In this note we show the decidability of the Clark's completion semantics for monadic general programs and queries. To appear in Theory and Practice of Logic Programming (TPLP)
Filling a Hole in a Crease Pattern: Isometric Mapping from Prescribed Boundary Folding
Venue: arXiv cs.CG 2014
Year: 2014

Given a sheet of paper and a prescribed folding of its boundary, is there a way to fold the paper's interior without stretching so that the boundary lines up with the prescribed boundary folding? For polygonal boundaries nonexpansively folded at finitely many points, we prove that a consistent isometric mapping of the polygon interior always exists and is computable in polynomial time.
Cloud-based Privacy Preserving Image Storage, Sharing and Search
Venue: arXiv cs.CR 2014
Year: 2014

High-resolution cameras produce huge volume of high quality images everyday. It is extremely challenging to store, share and especially search those huge images, for which increasing number of cloud services are presented to support such functionalities. However, images tend to contain rich sensitive information (\eg, people, location and event), and people's privacy concerns hinder their readily participation into the services provided by untrusted third parties. In this work, we introduce PIC: a Privacy-preserving large-scale Image search system on Cloud. Our system enables efficient yet secure content-based image search with fine-grained access control, and it also provides privacy-preserving image storage and sharing among users. Users can specify who can/cannot search on their images when using the system, and they can search on others' images if they satisfy the condition specified by the image owners. Majority of the computationally intensive jobs are outsourced to the cloud side, and users only need to submit the query and receive the result throughout the entire image search. Specially, to deal with massive images, we design our system suitable for distributed and parallel computation and introduce several optimizations to further expedite the search process. We implement a prototype of PIC including both cloud side and client side. The cloud side is a cluster of computers with distributed file system (Hadoop HDFS) and MapReduce architecture (Hadoop MapReduce). The client side is built for both Windows OS laptops and Android phones. We evaluate the prototype system with large sets of real-life photos. Our security analysis and evaluation results show that PIC successfully protect the image privacy at a low cost of computation and communication.
Parallel Multiphysics Simulations of Charged Particles in Microfluidic Flows
Venue: arXiv cs.CE 2014
Year: 2014

The article describes parallel multiphysics simulations of charged particles in microfluidic flows with the waLBerla framework. To this end, three physical effects are coupled: rigid body dynamics, fluid flow modelled by a lattice Boltzmann algorithm, and electric potentials represented by a finite volume discretisation. For solving the finite volume discretisation for the electrostatic forces, a cell-centered multigrid algorithm is developed that conforms to the lattice Boltzmann meshes and the parallel communication structure of waLBerla. The new functionality is validated with suitable benchmark scenarios. Additionally, the parallel scaling and the numerical efficiency of the algorithms are analysed on an advanced supercomputer.
Augmenting Ordered Binary Decision Diagrams with Conjunctive Decomposition
Venue: arXiv cs.AI 2014
Year: 2014

This paper augments OBDD with conjunctive decomposition to propose a generalization called OBDD[$\wedge$]. By imposing reducedness and the finest $\wedge$-decomposition bounded by integer $i$ ($\wedge_{\widehat{i}}$-decomposition) on OBDD[$\wedge$], we identify a family of canonical languages called ROBDD[$\wedge_{\widehat{i}}$], where ROBDD[$\wedge_{\widehat{0}}$] is equivalent to ROBDD. We show that the succinctness of ROBDD[$\wedge_{\widehat{i}}$] is strictly increasing when $i$ increases. We introduce a new time-efficiency criterion called rapidity which reflects that exponential operations may be preferable if the language can be exponentially more succinct, and show that: the rapidity of each operation on ROBDD[$\wedge_{\widehat{i}}$] is increasing when $i$ increases; particularly, the rapidity of some operations (e.g., conjoining) is strictly increasing. Finally, our empirical results show that: a) the size of ROBDD[$\wedge_{\widehat{i}}$] is normally not larger than that of the equivalent \ROBDDC{\widehat{i+1}}; b) conjoining two ROBDD[$\wedge_{\widehat{1}}$]s is more efficient than conjoining two ROBDD[$\wedge_{\widehat{0}}$]s in most cases, where the former is NP-hard but the latter is in P; and c) the space-efficiency of ROBDD[$\wedge_{\widehat{\infty}}$] is comparable with that of d-DNNF and that of another canonical generalization of \ROBDD{} called SDD.
Optimal online and offline algorithms for robot-assisted restoration of barrier coverage
Venue: arXiv cs.DS 2014
Year: 2014

Cooperation between mobile robots and wireless sensor networks is a line of research that is currently attracting a lot of attention. In this context, we study the following problem of barrier coverage by stationary wireless sensors that are assisted by a mobile robot with the capacity to move sensors. Assume that $n$ sensors are initially arbitrarily distributed on a line segment barrier. Each sensor is said to cover the portion of the barrier that intersects with its sensing area. Owing to incorrect initial position, or the death of some of the sensors, the barrier is not completely covered by the sensors. We employ a mobile robot to move the sensors to final positions on the barrier such that barrier coverage is guaranteed. We seek algorithms that minimize the length of the robot's trajectory, since this allows the restoration of barrier coverage as soon as possible. We give an optimal linear-time offline algorithm that gives a minimum-length trajectory for a robot that starts at one end of the barrier and achieves the restoration of barrier coverage. We also study two different online models: one in which the online robot does not know the length of the barrier in advance, and the other in which the online robot knows the length of the barrier. For the case when the online robot does not know the length of the barrier, we prove a tight bound of $3/2$ on the competitive ratio, and we give a tight lower bound of $5/4$ on the competitive ratio in the other case. Thus for each case we give an optimal online algorithm.