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What is it that makes movement around obstacles hard? The answer seems clear: obstacles contort the geometry of the workspace and make it difficult to leverage what we consider easy and intuitive straight-line Cartesian geometry. But is Cartesian motion actually easy? It's certainly well-understood and has numerous applications. But beneath the details of linear algebra and pseudoinverses, lies a...
We define a distance between two uncertain LTI systems1 which provides an upper bound on the difference in worst case robust performance when the same feedback controller is used with each system. We also suggest ways of using this measure to approximate complex uncertainty descriptions with simpler ones, with a view to simplifying any subsequent robust control design step.
Visual inference over a transmission channel is increasingly becoming an important problem in a variety of applications. In such applications, low latency and bit-rate consumption are often critical performance metrics, making data compression necessary. In this paper, we examine feature compression for support vector machine (SVM)-based inference using quantized randomized embeddings. We demonstrate...
To state whether a System Under Test is sufficiently tested requires an assessment of the test suite quality. Existing methods to assess the quality of a test suite either are based on the structure of an implementation or determine the quality using mutation score. In this paper we introduce a method, which is based on inductive inference to assess the quality of a test suite and propose a method...
It is vital to find a path that satisfies multiple Quality-of-Service (QoS) constraints with the deployment of current emerged services. However, it is not very efficient and effective at finding such a path for existing algorithms. In this paper, an improved version of fully polynomial time approximation scheme (IFPTAS) for multiple constraints path optimal (MCOP) problem was proposed. We find that...
Terrain affects connectivity in mobile ad hoc networks (MANET). Both average pair wise link closure and the rate at which the link-state changes when nodes move depend on the characteristics of the intervening terrain. Even though these key parameters depend only mildly on inter node distances in common real-world terrains, empirical analysis finds that the number of connected components in the network...
The “sparsity” challenge is a well-known problem in recommender systems. This issue relates to little information about each user or item in large data set. The purpose of this paper is pre-processing of data and using Non negative Matrix Factorization (NMF) method to improve this challenge. Since the original data are non negative, the algorithm based on NMF maintains positive effect of data on decomposition...
Linear programming has played a key role in the study of algorithms for combinatorial optimization problems. In the field of approximation algorithms, this is well illustrated by the uncapacitated facility location problem. A variety of algorithmic methodologies, such as LP-rounding and primal-dual method, have been applied to and evolved from algorithms for this problem. Unfortunately, this collection...
We address in this paper the problem of efficiently finding a few number of representative frequent itemsets in transaction matrices. To do so, we propose to rely on matrix decomposition techniques, and more precisely on Constrained Binary Matrix Factorization (CBMF) which decomposes a given binary matrix into the product of two lower dimensional binary matrices, called factors. We first show, under...
With more and more news sources publishing news articles online, news recommendation systems are becoming increasingly popular in recent days. However, if a news recommender shows to the user many news articles that cover same story or talk about same persons or events, then the recommendations might become monotonous for the user. A possible way to handle this scenario is to diversify the recommended...
Multi-robot patrolling is a problem that has important applications in security and surveillance. However, the optimal task assignment is known to be NP-hard. We consider evenly spacing the robots in a cyclic Traveling Salesman Problem (TSP) tour or partitioning the graph of the environment. The trade-off in performance, overall team travel cost and coordination is analyzed in this paper. We provide...
We propose a new metric for quantifying per-element distortion that is simple, intuitive and well-defined for both small- and large-signal excitations. Traditional distortion concepts, based on polynomial expansions and Volterra series, can be viewed as an approximation of our new metric. Although computing this metric exactly is quadratic in circuit size, we devise a novel approximation that (unlike...
Fuzzy clustering which can implement flexible classification is very useful but sometimes calculates the degrees of belongingness of an objects to a cluster too exactly. To solve this problem, a new clustering method called rough k-means (RKM) is proposed by Lingras et al. RKM which is an extended method by using rough set representation can classify more roughly than fuzzy clustering without lack...
Decision-making is one of the most common activities in human resource allocation, transportation, and many other areas. In real problems, the decision-making problems often involve uncertainty such as roughness and fuzziness. Therefore, a proper uncertainty descriptive method is the foundation of complex decision-making problems. In this paper, we use rough fuzzy set to describe the uncertainty....
Often new insights and advancements are made by a detailed study of the problem and the solution space. The area of community finding has had many algorithms proposed recently, but to our knowledge there have not been any detailed studies of the solution space. In this paper, we present two algorithms for enumerating and unranking the possible valid community assignments for a network. To demonstrate...
Service providers face multiple challenges in hosting an increasing number of virtual machine (VM) instances. Minimizing the utilization of system resources while maximizing the potential for profit are among the most common challenges. Recent studies have investigated memory reclamation techniques focused on virtual technologies, specifically page sharing, for minimizing the utilization of system...
Identifying nodes that play important roles in network dynamics in large scale complex networks is crucial for both characterizing the network and resource management. Under the viral marketing setting, Diffusion Centrality (DC) estimates the influential power of an individual. For the transport and physics communities, a node is considered important in Markov centrality (MC) if it can be quickly...
Person re-identification is a challenging problem in multi-camera surveillance systems. Most current methods always aim at learning a global distance metric to overcome the visual appearance changes between images from different cameras. However, the feature variations between images are not constant over the entire feature space, thus one global metric is not always applicable to all feature variation...
Based on granular space, the hierarchical structure invariance and optimal approximation for proximity data are presented, and four results are obtained as follows. Firstly, an improved algorithm for computing the hierarchical structure and the related min-transitive closure of a fuzzy proximity relation are given, and the properties of key point sequence are studied by introducing the key points...
Prior art in approximate computing has extensively studied computational resilience to imprecision. However, existing approaches often rely on static techniques, which potentially compromise coverage and reliability. Our approach, on the other hand, decouples error analysis of the approximate accelerator from quality analysis of the overall application. We use high-level, application-specific metrics,...
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