We propose four new structural decomposition techniques for Constraint Satisfaction Problems. We compare these four techniques both theoretically and experimentally with hinge decomposition and hypertree decomposition. Our experiments show that one of our techniques offers the best trade-off between the computational cost of the decomposition and the width of the resulting decomposition tree.

The proper generalized decomposition (PGD) aims at finding the solution of a generic problems into a low rank approximation. On the contrary to the singular value decomposition (SVD), such a low rank approximation is generally not the optimal one leading to memory issues and loss of computational efficiency. Nonetheless, the computational cost of the SVD is generally prohibitive to be performed...

Recent SVD-free matrix factorization formulations have enabled rank optimization for extremely large-scale systems (millions of rows and columns). In this paper, we consider rank-regularized formulations that only require a target data-fitting error level, and propose an algorithm for the corresponding problem. We illustrate the advantages of the new approach using the Netflix problem, and use ...

This paper presents a simple method for mining both positive and negative association rules in databases using singular value decomposition (SVD) and similarity measures. In literature, SVD is used for summarizing matrices. We use transaction-item price matrix to generate so called ratio rules in the literature. Transaction-item price matrix is formed by using the price data of corresponding it...

Protection of privacy from unauthorized access is one of the primary concerns in data use, from national security to business transactions. It brings out a new branch of data mining, known as Privacy Preserving Data Mining (PPDM). Privacy-Preserving is a major concern in the application of data mining techniques to datasets containing personal, sensitive, or confidential information. Data disto...

The spectral radius of the adjacency matrix can impact both algorithmic efficiency as well as the stability of solutions to an underlying dynamical process. Although much research has considered the distribution of the spectral radius for undirected random graph models, as symmetric adjacency matrices are amenable to spectral analysis, very little work has focused on directed graphs. Consequent...

in order to implement the cellular manufacturing system in practice, some essential factors should be taken into account. in this paper, a new mathematical model for cellular manufacturing system considering different production factors including alternative process routings and machine reliability with stochastic arrival and service times in a dynamic environment is proposed. also because of t...

The integrated aircraft routing and crew scheduling problem consists in determining a minimum-cost set of aircraft routes and crew pairings such that each 1ight leg is covered by one aircraft and one crew, and side constraints are satis2ed. While some side constraints involve only crews or aircraft, linking constraints impose minimum connection times for crews that depend on aircraft connection...

Entropy based phase shift migration with de-noising algorithm for radar body area focusing imaging Hui Zhang, Yun Lu and Dirk Plettemeier Off-body Channel Measurements at 2.4 GHz and 868 MHz in an Indoor Environment Evangelos Mellios, Angelos Goulianos, Sema Dumanli, Geoffrey Hilton, Robert Piechocki and Ian Craddock Radar vertebral column imaging by inhomogeneous medium radar focusing algorith...

The Singular Value Decomposition is a key operation in many machine learning methods. Its computational cost, however, makes it unscalable and impractical for applications involving large datasets or real-time responsiveness, which are becoming increasingly common. We present a new method, QUIC-SVD, for fast approximation of the whole-matrix SVD based on a new sampling mechanism called the cosi...