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arXiv 2025年

作者： Woodruff, David P. Xie, Shenghao Zhou, Samson Carnegie Mellon University Google Research United States Texas A&M University United States

Given a vector x ∈ Rn induced by a turnstile stream S, a non-negative function G : R → R, a perfect G-sampler outputs an index i with probability[Formula presented]Jayaram and Woodruff (FOCS 2018) introduced a perfect Lp-sampler, where G(z) = |z|p, for p ∈ (0, 2]. In this paper, we solve this problem for p > 2 by a sampling-and-rejection method. Our algorithm runs in n1−2/p · polylog(n) bits of space, which is tight up to polylogarithmic factors in n. Our algorithm also provides a (1 + Ε)-approximation to the sampled item xi with high probability using an additional Ε−2n1−2/p · polylog(n) bits of space. Interestingly, we show our techniques can be generalized to perfect polynomial samplers on turnstile streams, which is a class of functions that is not scale-invariant, in contrast to the existing perfect Lp samplers. We also achieve perfect samplers for the logarithmic function G(z) = log(1 + |z|) and the cap function G(z) = min(T, |z|p). Finally, we give an application of our results to the problem of norm/moment estimation for a subset Q of coordinates of a vector, revealed only after the data stream is processed, e.g., when the set Q represents a range query, or the set n \ Q represents a collection of entities who wish for their information to be expunged from the dataset. © 2025, CC BY.

关键词： approximation algorithms

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Solving Drone Routing Problems with Quantum Computing: A Hybrid Approach Combining Quantum Annealing and Gate-Based Paradigms

Solving Drone Routing Problems with Quantum Computing: A Hyb...

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Congress on Evolutionary Computation

作者： Eneko Osaba Pablo Miranda-Rodriguez Andreas Oikonomakis Matic Petrič Alejandra Ruiz Sebastian Bock Michail-Alexandros Kourtis TECNALIA Basque Research and Technology Alliance (BRTA) Derio Spain National Centre for Scientific Research Demokritos Greece Fraunhofer Institute for Open Communication Systems (FOKUS) Berlin Germany

ISBN: (数字)9798331534318

ISBN: (纸本)9798331534325

This paper presents a novel hybrid approach to solving real-world drone routing problems by leveraging the capabilities of quantum computing. The proposed method, coined Quantum for Drone Routing (Q4DR), integrates the two most prominent paradigms in the field: quantum gate-based computing, through the Eclipse Qrisp programming language; and quantum annealers, by means of D-Wave System’s devices. The algorithm is divided into two different phases: an initial clustering phase executed using a Quantum Approximate Optimization Algorithm (QAOA), and a routing phase employing quantum annealers. The efficacy of Q4DR is demonstrated through three use cases of increasing complexity, each incorporating real-world constraints such as asymmetric costs, forbidden paths, and itinerant charging points. This research contributes to the growing body of work in quantum optimization, showcasing the practical applications of quantum computing in logistics and route planning.

关键词： Annealing Clustering algorithms Logic gates Routing Quantum annealing approximation algorithms Planning Optimization Drones Logistics

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Spectrum and RFI Sensing using 2.4 GHz Digital Multi-Beam Circular Apertures with 360 FoV

Spectrum and RFI Sensing using 2.4 GHz Digital Multi-Beam Ci...

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IEEE Space Hardware and Radio Conference (SHaRC)

作者： A. Madanayake B. Thevathasan C. Rathnayaka U. Kumarasiri S. Sivasankar V. Ariyarathna Department of Electrical and Computer Engineering Florida International University Miami USA

ISBN: (数字)9798331507367

ISBN: (纸本)9798331507374

Radio spectrum monitoring across 360-degree field-of-view (FoV) is a fundamental requirement for RF situational awareness. RF awareness demands sensed intelligence on the direction of arrival, frequency occupancy, modulation type signal power, and bandwidth for each waveform present. This article includes an end-to-end design and realization of an array processor, consisting of sixteen uniformly spaced antennas in a circular array at 2.4 GHz, providing 360-degrees FoV using digital multi-beam beamforming. The algorithms encapsulate a low-complexity multi-beam circular array processor with each RF beam being processed by an approximate discrete Fourier transform (ADFT) algorithm. All directional sensing covered by sixteen simultaneous RF beams are 100 MHz in baseband. A fully parallel systolic-array processor for multi-beams is realized using Xilinx Virtex-6 FPGA and CASPER toolchain.

关键词： Radio frequency Array signal processing Bandwidth Parallel processing approximation algorithms Hardware Sensors Monitoring Antenna arrays Radiofrequency interference

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Design and Evaluation of a Radar Task Scheduling Algorithm Based on Gaussian Random Perturbation

Design and Evaluation of a Radar Task Scheduling Algorithm B...

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Electrical, Electronic Information and Communication Engineering (EEICE), International Conference on

作者： Xinyu Wang Jianming Zhou Ning Chen Shiqi Wu School of Integrated Circuits and Electronics Beijing Institute of Technology (BIT) Beijing China

ISBN: (数字)9798331532598

ISBN: (纸本)9798331532604

Task scheduling in multifunction radar systems (MFRs) is a typical combinatorial optimization problem characterized by NP-hard complexity. Traditional exact methods entail high computational complexity, making them unsuitable for real-time applications. This paper presents a heuristic radar task scheduling algorithm based on Gaussian random perturbations. The algorithm introduces priority-dependent stochastic offsets around the expected start times to initially generate a task sequence, and then dynamically updates the priorities and start times of remaining tasks according to their temporal urgency. Simulation results show that compared with traditional methods such as EST, ED, and heuristic algorithms including RSST and DSS, the proposed algorithm significantly reduces the overall scheduling cost by approximately 40% on average and improves the task success rate by about 5%-10%. Hardware validation on an FPGA platform operating at 400 MHz frequency with 350 iterations demonstrated approximately a 10% improvement in task scheduling success rate, confirming the effectiveness and real-time capability of the proposed method.

关键词： Costs Scheduling algorithms Heuristic algorithms Perturbation methods Radar approximation algorithms Scheduling Real-time systems Timing Field programmable gate arrays

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Group Formation algorithms

Group Formation Algorithms

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International Carpathian Control Conference (ICCC)

作者： Andrea Mojžišová Marcela Pavlíčková Institute of Control and Informatization of Production Processes Faculty of BERG Technical University of Košice Košice Slovakia

ISBN: (数字)9798331501273

ISBN: (纸本)9798331501280

Sharing knowledge among students, their mutual collaboration, communication, and responsibility for a common goal are skills that are developed through students’ group work on a project or lesson. These skills are important not only for personal growth but also for professional development. One of the key tasks for the effective implementation of group work in education is the formation of groups. This article examines most used algorithms for group formation and select suitable algorithm for our courses.

关键词： Ant colony optimization Metaheuristics Education Bibliometrics Clustering algorithms Collaboration approximation algorithms Particle swarm optimization Genetic algorithms

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Experimental Verification of a Mathematical Model for a Heat Store

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Russian Engineering Research 2021年第8期41卷 742-744页

作者： Sorokin, A.E. Moscow Aviation Institute Moscow Russia

Abstract: A method is proposed for the analysis of experimental data so as to verify the mathematical model of a heat store with a melting working medium. Topics considered include the verification of the experimental data;elimination of discrepant values;approximation of the experimental data;and verification of the approximate formula for the experimental data. © 2021, Allerton Press, Inc.

关键词： approximation algorithms

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Quaternionic Minkowski Reduction and Its Application in Dual-Polarized MIMO Systems

Quaternionic Minkowski Reduction and Its Application in Dual...

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International ITG Conference on Source and Channel Coding (SCC)

作者： Sebastian Stern Cong Ling Cornelia Ott Robert F.H. Fischer Institute of Communications Engineering Ulm University Germany Department of Electrical and Electronic Engineering Imperial College London United Kingdom Institute of Communications and Navigation German Aerospace Center (DLR) Germany

ISBN: (数字)9798331522896

ISBN: (纸本)9798331522902

The task of finding the shortest vectors of a lattice that form a basis thereof is known as Minkowski reduction. In this work, Minkowski reduction is adapted to discrete subgroups of quaternionic spaces defined over the set of Hurwitz integers which constitutes a Euclidean subring of the (Hamilton) quaternions. Based on a quaternionic variant of Minkowski's greatest-common-divisor condition for suitable lattice vectors, a lattice-basis-reduction algorithm is derived. To that end, a basisupdate approach is presented which takes the non-commutativity of quaternionic multiplication into account. The reduction algorithm is finally applied in multi-user multiple-input/multipleoutput (MIMO) systems with dual-polarized antennas, where the quaternionic interference is handled by lattice-reduction-aided equalization. It is shown that quaternionic Minkowski reduction achieves significantly better results than state-of-the-art Lenstra-Lenstra-Lovász (LLL) reduction and that the successive minima of quaternionic lattices are approximated quite well.

关键词： Quaternions Lattices Interference approximation algorithms Vectors MIMO Encoding Antennas

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Algorithm Design for Continual Learning in IoT Networks

Algorithm Design for Continual Learning in IoT Networks

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Shugang Hao Lingjie Duan Pillar of Engineering Systems and Design Singapore University of Technology and Design

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Continual learning (CL) is a new online learning technique over sequentially generated streaming data from different tasks, aiming to maintain a small forgetting loss on previously-learned tasks. Existing work focuses on reducing the forgetting loss under a given task sequence. However, if similar tasks continuously appear to the end time, the forgetting loss is still huge on prior distinct tasks. In practical IoT networks, an autonomous vehicle to sample data and learn different tasks can route and alter the order of task pattern at increased travelling cost. To our best knowledge, we are the first to study how to opportunistically route the testing object and alter the task sequence in CL. We formulate a new optimization problem and prove it NP-hard. We propose a polynomial-time algorithm to achieve approximation ratios of $\frac{3}{2}$ for underparameterized case and $\frac{3}{2} + {r^{1 - T}}$ for overparameterized case, respectively. Simulation results verify our algorithm’s close-to-optimum performance.

关键词： Continuing education Costs Simulation Signal processing algorithms Signal processing approximation algorithms Polynomials Speech processing Optimization Testing

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Redefining Platform Data Mining Paradigms with Sequential Quadratic Programming Considering Optimization Models

Redefining Platform Data Mining Paradigms with Sequential Qu...

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Sentiment Analysis and Deep Learning (ICSADL), International Conference on

作者： Xiong Wenting Guangdong University of Science and Technology Dongguan Guangdong China

ISBN: (数字)9798331523923

ISBN: (纸本)9798331523930

Platform data mining is an important branch of data analysis. Traditional methods such as clustering have achieved satisfactory performance. To overcome the shortcomings of traditional algorithms in mathematical optimization, this study proposes a novel model based on the sequential quadratic programming algorithm. At the algorithm level, this study first analyses the characteristics of cloud platform data and its requirements for mining efficiency. At the same time, to solve these problems, this study proposed a new data analysis framework that combines sparse factor analysis and embedded database subspace detection. The designed model optimizes attribute dimension selection and dense region extraction to the greatest extent through distribution analysis and feature correlation evaluation. At the same time, the Bayesian network node expansion algorithm is used to model the association of discrete data, and then a cascade data generation method is designed based on this model. Finally, the Bayesian network parameters are optimized by the sequential quadratic programming algorithm, and the approximate value of the Hessian matrix is efficiently solved by the BFGS algorithm, thereby improving the accuracy of the data mining algorithm. The experimental part uses the cloud platform data-set as the target data-set and verifies the stability of the proposed algorithm.

关键词： Cloud computing Heuristic algorithms Computational modeling Clustering algorithms approximation algorithms Feature extraction Data models Data mining Quadratic programming Optimization

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Embedding Graphs as Euclidean kNN-Graphs

arXiv

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arXiv 2025年

作者： Schibler, Thomas Suri, Subhash Xue, Jie University of California Santa BarbaraCA United States New York University Shanghai China

Let G = (V, E) be a directed graph on n vertices where each vertex has out-degree k. We say that G is kNN-realizable in d-dimensional Euclidean space if there exists a point set P = {p1, p2, . . ., pn} in Rd along with a one-to-one mapping : V → P such that for any u, v ∈ V , u is an out-neighbor of v in G if and only if (u) is one of the k nearest neighbors of (v);we call the map a kNN-realization of G in Rd. The kNN-realization problem, which aims to compute a kNN-realization of an input graph in Rd, is known to be NP-hard already for d = 2 and k = 1 [Eades and Whitesides, Theoretical Computer Science, 1996], and to the best of our knowledge has not been studied in dimension d = 1. The main results of this paper are the following: For any fixed dimension d ≥ 2, we can efficiently compute an embedding realizing at least a 1 − Ε fraction of G’s edges, or conclude that G is not kNN-realizable in Rd. For d = 1, we can decide in O(kn) time whether G is kNN-realizable and, if so, compute a realization in O(n2.5poly(log n)) time. © 2025, CC BY.

关键词： approximation algorithms

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