A new curve fitting based rating prediction algorithm for recommender systems

Yilmaz Ar; Şahin Emrah Amrahov; Nizami A. Gasilov; Sevgi Yigit-Sert

Displaying similar documents to “A new curve fitting based rating prediction algorithm for recommender systems”

A New overlapping community detection algorithm based on similarity of neighbors in complex networks

Pelin Çetin, Sahin Emrah Amrahov (2022)

Kybernetika

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Community detection algorithms help us improve the management of complex networks and provide a clean sight of them. We can encounter complex networks in various fields such as social media, bioinformatics, recommendation systems, and search engines. As the definition of the community changes based on the problem considered, there is no algorithm that works universally for all kinds of data and network structures. Communities can be disjointed such that each member is in at most one...

Safe consensus control of cooperative-competitive multi-agent systems via differential privacy

Jiayue Ma, Jiangping Hu (2022)

Kybernetika

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This paper investigates a safe consensus problem for cooperative-competitive multi-agent systems using a differential privacy (DP) approach. Considering that the agents simultaneously interact cooperatively and competitively, we propose a novel DP bipartite consensus algorithm, which guarantees that the DP strategy only works on competitive pairs of agents. We then prove that the proposed algorithm can achieve the mean square bipartite consensus and $(p, r)$ -accuracy. Furthermore, a differential...

On the weighted Euclidean matching problem in $ℝ^{d}$

Birgit Anthes, Ludger Rüschendorf (2001)

Applicationes Mathematicae

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A partitioning algorithm for the Euclidean matching problem in $ℝ^{d}$ is introduced and analyzed in a probabilistic model. The algorithm uses elements from the fixed dissection algorithm of Karp and Steele (1985) and the Zig-Zag algorithm of Halton and Terada (1982) for the traveling salesman problem. The algorithm runs in expected time $n {(l o g n)}^{p - 1}$ and approximates the optimal matching in the probabilistic sense.

A viscosity-proximal gradient method with inertial extrapolation for solving certain minimization problems in Hilbert space

L.O. Jolaoso, H.A. Abass, O.T. Mewomo (2019)

Archivum Mathematicum

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In this paper, we study the strong convergence of the proximal gradient algorithm with inertial extrapolation term for solving classical minimization problem and finding the fixed points of $δ$ -demimetric mapping in a real Hilbert space. Our algorithm is inspired by the inertial proximal point algorithm and the viscosity approximation method of Moudafi. A strong convergence result is achieved in our result without necessarily imposing the summation condition $\sum_{n = 1}^{\infty} β_{n} ∥ x_{n - 1} - x_{n} ∥ < + \infty$ on the inertial term. Finally,...

A branch and bound algorithm for the two-machine flowshop problem with unit-time operations and time delays

Aziz Moukrim, Djamal Rebaine, Mehdi Serairi (2014)

RAIRO - Operations Research - Recherche Opérationnelle

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In this paper we consider the problem of scheduling, on a two-machine flowshop, a set of unit-time operations subject to time delays with respect to the makespan. This problem is known to be $𝒩 P$ x1d4a9;x1d4ab; -hard in the strong sense. We propose an algorithm based on a branch and bound enumeration scheme. This algorithm includes the implementation of new lower and upper bound procedures, and dominance rules. A computer simulation to measure the performance of the algorithm is provided...

An interior-point algorithm for semidefinite least-squares problems

Chafia Daili, Mohamed Achache (2022)

Applications of Mathematics

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We propose a feasible primal-dual path-following interior-point algorithm for semidefinite least squares problems (SDLS). At each iteration, the algorithm uses only full Nesterov-Todd steps with the advantage that no line search is required. Under new appropriate choices of the parameter $β$ which defines the size of the neighborhood of the central-path and of the parameter $θ$ which determines the rate of decrease of the barrier parameter, we show that the proposed algorithm is well defined...

A modified K3M thinning algorithm

Marek Tabedzki, Khalid Saeed, Adam Szczepański (2016)

International Journal of Applied Mathematics and Computer Science

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The K3M thinning algorithm is a general method for image data reduction by skeletonization. It had proved its feasibility in most cases as a reliable and robust solution in typical applications of thinning, particularly in preprocessing for optical character recognition. However, the algorithm had still some weak points. Since then K3M has been revised, addressing the best known drawbacks. This paper presents a modified version of the algorithm. A comparison is made with the original...

Constrained $𝐤$ -means algorithm for resource allocation in mobile cloudlets

Rasim M. Alguliyev, Ramiz M. Aliguliyev, Rashid G. Alakbarov (2023)

Kybernetika

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With the rapid increase in the number of mobile devices connected to the Internet in recent years, the network load is increasing. As a result, there are significant delays in the delivery of cloud resources to mobile users. Edge computing technologies (edge, cloudlet, fog computing, etc.) have been widely used in recent years to eliminate network delays. This problem can be solved by allocating cloud resources to the cloudlets that are close to users. The article proposes a clustering-based...

Distributed accelerated Nash equilibrium learning for two-subnetwork zero-sum game with bilinear coupling

Xianlin Zeng, Lihua Dou, Jinqiang Cui (2023)

Kybernetika

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This paper proposes a distributed accelerated first-order continuous-time algorithm for $O (1 / t^{2})$ convergence to Nash equilibria in a class of two-subnetwork zero-sum games with bilinear couplings. First-order methods, which only use subgradients of functions, are frequently used in distributed/parallel algorithms for solving large-scale and big-data problems due to their simple structures. However, in the worst cases, first-order methods for two-subnetwork zero-sum games often have an asymptotic...

A descent algorithm for $ε$ - approximation of continuous functions with values in unitary space

M. Janc (1982)

Matematički Vesnik

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Derivation of BiCG from the conditions defining Lanczos' method for solving a system of linear equations

Petr Tichý, Jan Zítko (1998)

Applications of Mathematics

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Lanczos’ method for solving the system of linear algebraic equations $A x = b$ consists in constructing a sequence of vectors $x_{k}$ in such a way that $r_{k} = b - A x_{k} \in r_{0} + A 𝒦_{k} (A, r_{0})$ and $r_{k} ⊥ 𝒦_{k} (A^{T}, {\tilde{r}}_{0})$ . This sequence of vectors can be computed by the BiCG (BiOMin) algorithm. In this paper is shown how to obtain the recurrences of BiCG (BiOMin) directly from this conditions.

A clustering approach using cooperative artificial bee colony algorithm.

Zou, Wenping, Zhu, Yunlong, Chen, Hanning, Sui, Xin (2010)

Discrete Dynamics in Nature and Society

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On the power of randomization for job shop scheduling with $k$ -units length tasks

Tobias Mömke (2009)

RAIRO - Theoretical Informatics and Applications - Informatique Théorique et Applications

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In the job shop scheduling problem $k$ -units- $J_{m}$ , there are $m$ machines and each machine has an integer processing time of at most $k$ time units. Each job consists of a permutation of $m$ tasks corresponding to all machines and thus all jobs have an identical dilation $D$ . The contribution of this paper are the following results; (i) for $d = o (\sqrt{D})$ jobs and every fixed $k$ , the makespan of an optimal schedule is at most $D + o (D)$ , which extends the result of [3] for $k = 1$ ; (ii) a randomized on-line approximation algorithm...

A remark on Tate's algorithm and Kodaira types

Tim Dokchitser, Vladimir Dokchitser (2013)

Acta Arithmetica

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We remark that Tate’s algorithm to determine the minimal model of an elliptic curve can be stated in a way that characterises Kodaira types from the minimum of $v (a_{i}) / i$ . As an application, we deduce the behaviour of Kodaira types in tame extensions of local fields.