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检索条件"任意字段=Symposium on Discrete Algorithms"

共 2733 条记录，以下是81-90 订阅

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Performance of FPGA-based Implementations of Data Classification Techniques using HDL Coder

Performance of FPGA-based Implementations of Data Classifica...

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IEEE International symposium on Intelligent Signal Processing and Communication Systems (ISPACS)

作者： Adil Zafar Hen-Geul Yeh Dept. of Electrical Engineering California State University Long Beach Long Beach USA

ISBN: (数字)9798350389210

ISBN: (纸本)9798350389227

The aim of this tutorial paper is to check the efficiency of data classification techniques implemented on a field programmable gate array (FPGA) using a high-level synthesis (HLS) tool. We implement data classification techniques using Simulink with HDL Coder onto a Basys 3 FPGA board. Using a scalable and modular approach, three different algorithms are implemented in this paper with varying parameters, and their resource utilization is recorded. The three algorithms are the fast Fourier transform (FFT), the discrete cosine transform (DCT), and the K-Nearest Neighbor (KNN) algorithm.

关键词： Fast Fourier transforms Software packages Signal processing algorithms Tutorials Nearest neighbor methods Signal processing Classification algorithms discrete cosine transforms Hardware design languages Field programmable gate arrays

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18th International symposium on algorithms and Data Structures, WADS 2023

18th International Symposium on Algorithms and Data Structur...

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18th International symposium on algorithms and Data Structures, WADS 2023

ISBN: (纸本)9783031389054

The proceedings contain 47 papers. The special focus in this conference is on algorithms and Data Structures. The topics include: Compact Distance Oracles with Large Sensitivity and Low Stretch;finding Diameter-Reducing Shortcuts in Trees;approximating the Smallest k-Enclosing Geodesic Disc in a Simple Polygon;online Interval Scheduling with Predictions;on Length-Sensitive Fréchet Similarity;hardness of Graph-Structured Algebraic and Symbolic Problems;sublinear-Space Streaming algorithms for Estimating Graph Parameters on Sparse Graphs;efficient k-Center algorithms for Planar Points in Convex Position;classification via Two-Way Comparisons (Extended Abstract);the Mutual Visibility Problem for Fat Robots;improved Bounds for discrete Voronoi Games;general Space-Time Tradeoffs via Relational Queries;approximate Minimum Sum Colorings and Maximum k-Colorable Subgraphs of Chordal Graphs;differentially Private Range Query on Shortest Paths;revisiting Graph Persistence for Updates and Efficiency;block Crossings in One-Sided Tanglegrams;observation Routes and External Watchman Routes;lower Bounds for Non-adaptive Shortest Path Relaxation;shortest Coordinated Motion for Square Robots;linear Layouts of Bipartite Planar Graphs;faster algorithms for Cycle Hitting Problems on Disk Graphs;adaptive Data Structures for 2D Dominance Colored Range Counting;zip-Zip Trees: Making Zip Trees More Balanced, Biased, Compact, or Persistent;external-Memory Sorting with Comparison Errors;verifying the Product of Generalized Boolean Matrix Multiplication and Its Applications to Detect Small Subgraphs;reconfiguration of Time-Respecting Arborescences;algorithmic Theory of Qubit Routing;3-Coloring C4 or C3 -Free Diameter Two Graphs;colored Constrained Spanning Tree on Directed Graphs;geometric Hitting Set for Line-Constrained Disks;An ETH-Tight Algorithm for Bidirected Steiner Connectivity;tight Analysis of the Lazy Algorithm for Open Online Dial-a-Ride;from Curves to Words and Back Again: Geometr

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ISSAC 2023 - Proceedings of the 2023 International symposium on Symbolic and Algebraic Computation

ISSAC 2023 - Proceedings of the 2023 International Symposium...

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48th International symposium on Symbolic and Algebraic Computation, ISSAC 2023

ISBN: (纸本)9798400700392

The proceedings contain 62 papers. The topics discussed include: the complexity of diagonalization;least distortion Euclidean embeddings of flat tori;matrix structures and matrix functions;invariants: computation and applications;algebra-based loop analysis;the tropical Nullstellensatz and Positivstellensatz for sparse polynomial systems;moment varieties for mixtures of products;an algorithm to enumerate grid signed permutation classes;beating binary powering for polynomial matrices;fast algorithms for discrete differential equations;validated root enclosures for interval polynomials with multiplicities;generalized cone complexes and tropical moduli in Polymake;real zeros of mixed random fewnomial systems;certified simultaneous isotopic approximation of pairs of curves via subdivision;and isolating clusters of zeros of analytic systems using arbitrary-degree inflation.

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Learning Low-Degree Functions from a Logarithmic Number of Random Queries 2022

Learning Low-Degree Functions from a Logarithmic Number of R...

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54th Annual ACM SIGACT symposium on Theory of Computing (STOC)

作者： Eskenazis, Alexandros Ivanisvili, Paata Univ Cambridge Cambridge England Univ Calif Irvine Irvine CA USA

We prove that every bounded function f : {-1, 1}(n) -> [-1, 1] of degree at most d can be learned with L2-accuracy e and confidence 1 - delta from log( n/delta) epsilon C--d-1(d3/2)root log d random queries, where ... 详细信息

ISBN: (纸本)9781450392648

关键词： discrete hypercube learning theory Bohnenblust-Hille inequality

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STOC 2023 - Proceedings of the 55th Annual ACM symposium on Theory of Computing

STOC 2023 - Proceedings of the 55th Annual ACM Symposium on ...

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55th Annual ACM symposium on Theory of Computing, STOC 2023

ISBN: (纸本)9781450399135

The proceedings contain 155 papers. The topics discussed include: almost Chor-Goldreich sources and adversarial random walks;a new Berry-Esseen Theorem for expander walks;near-optimal derandomization of medium-width branching programs;approximating iterated multiplication of stochastic matrices in small space;when Arthur has neither random coins nor time to spare: superfast derandomization of proof systems;exact phase transitions for stochastic block models and reconstruction on trees;parallel discrete sampling via continuous walks;sampling from convex sets with a cold start using multiscale decompositions;on regularity lemma and barriers in streaming and dynamic matching;optimal eigenvalue approximation via sketching;(noisy) gap cycle counting strikes back: random order streaming lower bounds for connected components and beyond;chaining, group leverage score overestimates, and fast spectral hypergraph sparsification;locally consistent decomposition of strings with applications to edit distance sketching;and sublinear time algorithms and complexity of approximate maximum matching.

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Determinant Maximization via Matroid Intersection algorithms 63

Determinant Maximization via Matroid Intersection Algorithms

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63rd Annual IEEE symposium on Foundations of Computer Science (FOCS)

作者： Brown, Adam Laddha, Aditi Pittu, Madhusudhan Singh, Mohit Tetali, Prasad Georgia Inst Technol Sch Math Atlanta GA 30332 USA Georgia Inst Technol Coll Comp Atlanta GA 30332 USA Carnegie Mellon Univ Sch Comp Sci Pittsburgh PA 15213 USA Georgia Inst Technol H Milton Stewart Sch Ind & Syst Engn Atlanta GA 30332 USA Carnegie Mellon Univ Math Sci Pittsburgh PA 15213 USA

ISBN: (纸本)9781665455190

Determinant maximization problem gives a general framework that models problems arising in as diverse fields as statistics [1], convex geometry [2], fair allocations [3], combinatorics [4], spectral graph theory [5], network design, and random processes [6]. In an instance of a determinant maximization problem, we are given a collection of vectors U = {nu(1),..., nu(n)} subset of R-d, and a goal is to pick a subset S subset of U of given vectors to maximize the determinant of the matrix Sigma(i is an element of S) nu(i)nu(inverted perpendicular)(i). Often, the set S of picked vectors must satisfy additional combinatorial constraints such as cardinality constraint (|S| <= k) or matroid constraint ( S is a basis of a matroid defined on the vectors). In this paper, we give a polynomial-time deterministic algorithm that returns a r(O(r))-approximation for any matroid of rank r <= d. This improves previous results that give e(O(r2))-approximation algorithms relying on e(O(r))-approximate estimation algorithms [4], [7]-[9] for any r <= d. All previous results use convex relaxations and their relationship to stable polynomials and strongly log-concave polynomials or non-convex relaxations for the problem [10]. In contrast, our algorithm builds on combinatorial algorithms for matroid intersection, which iteratively improve any solution by finding an alternating negative cycle in the exchange graph defined by the matroids. While the det(.) function is not linear, we show that taking appropriate linear approximations at each iteration suffice to give the improved approximation algorithm.

关键词： Computations on discrete structures Linear approximation Combinatorial algorithms

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Direct Batch Generation of Optimal Eigenvectors of the Symmetric Kernel of the discrete Hankel Transform

Direct Batch Generation of Optimal Eigenvectors of the Symme...

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Midwest symposium on Circuits and Systems (MWSCAS)

作者： Magdy Tawfik Hanna Department of Engineering Mathematics and Physics Fayoum University Fayoum Egypt

ISBN: (数字)9798350387179

ISBN: (纸本)9798350387186

1 - The development of the recently emergent discrete fractional Hankel transform (DFRHT) depends mainly on generating orthonormal eigenvectors of the kernel matrix of the discrete Hankel transform (DHT). For the DFRHT to approximate its continuous counterpart, the eigenvectors in question should approximate samples of the eigenfunctions of the Hankel transform (HT). The recently developed techniques for the generation of optimal eigenvectors of any unitary kernel matrix can be classified as either indirect (in the sense of first generating initial eigenvectors as a prerequisite for the generation of optimal ones) or direct (in the sense of not needing initial eigenvectors). Moreover, those techniques can be viewed as either batch or sequential. This paper's main objective is to assess the performance of the recently developed direct batch generation algorithms of optimal orthonormal eigenvectors of the symmetric kernel matrix of the DHT.

关键词： Symmetric matrices Circuits and systems Transforms DH-HEMTs Approximation error Approximation algorithms Vectors

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Optimizing over the Efficient Set of a Multi-Objective discrete Optimization Problem 21

Optimizing over the Efficient Set of a Multi-Objective Discr...

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21st International symposium on Experimental algorithms, SEA 2023

作者： Tamby, Satya Vanderpooten, Daniel Université Paris Dauphine PSL Research University LAMSADE France

ISBN: (纸本)9783959772792

Optimizing over the efficient set of a discrete multi-objective problem is a challenging issue. The main reason is that, unlike when optimizing over the feasible set, the efficient set is implicitly characterized. Therefore, methods designed for this purpose iteratively generate efficient solutions by solving appropriate single-objective problems. However, the number of efficient solutions can be quite large and the problems to be solved can be difficult practically. Thus, the challenge is both to minimize the number of iterations and to reduce the difficulty of the problems to be solved at each iteration. In this paper, a new enumeration scheme is proposed. By introducing some constraints and optimizing over projections of the search region, potentially large parts of the search space can be discarded, drastically reducing the number of iterations. Moreover, the single-objective programs to be solved can be guaranteed to be feasible, and a starting solution can be provided allowing warm start resolutions. This results in a fast algorithm that is simple to implement. Experimental computations on two standard multi-objective instance families show that our approach seems to perform significantly faster than the state of the art algorithm. © 2023 Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing. All rights reserved.

关键词： Multiobjective optimization

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Comparative Analysis of DFT and Quadrature Demodulation algorithms for Complex Spectrum Measurements

Comparative Analysis of DFT and Quadrature Demodulation Algo...

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International Scientific symposium on Metrology and Metrology Assurance (MMA)

作者： Sergey A. Podobuev Anna A. Krylovich Alexandra E. Evsenkina Alexander A. Shatokhin Nikolay A. Serov Andrey N. Serov Diagnostic Information Technologies Department National Research University “Moscow Power Engineering Institute” Moscow Russian Federation Computing Machines Systems and Networks Department National Research University “Moscow Power Engeneering Institute” Moscow Russian Federation

ISBN: (数字)9798350352832

ISBN: (纸本)9798350352849

To measure the signal spectrum, algorithms based on the implementation of the discrete Fourier transform and quadrature demodulation take place. All of the approaches under consideration are difficult to implement. In addition, the quadrature demodulation method has the potential to have significantly greater accuracy. The main reason for the occurrence of methodological measurement error in the case of DFT algorithms is the “spectrum leakage” effect. Estimating this error causes significant difficulties. The work shows that for the case of using a quadrature demodulator with an output filter of the moving average type, the discrete Fourier transform and the quadrature demodulator are mathematically equivalent. Simulation modeling of the most popular DFT implementation algorithms (direct implementation, Goertzel algorithm, DFT as filtering and fast Fourier transform) has been carried out. For the quadrature demodulation method, the influence of the output filter on the resulting error in measuring the amplitude and phase spectra of the signal is considered. The results of simulation and mathematical modeling were compared to confirm the reliability of the results.

关键词： Fast Fourier transforms discrete Fourier transforms Measurement uncertainty Filtering algorithms Length measurement Metrology Time measurement Mathematical models Frequency measurement Demodulation

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Maximal-Capacity discrete Memoryless Channel Identification

Maximal-Capacity Discrete Memoryless Channel Identification

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2023 IEEE International symposium on Information Theory, ISIT 2023

作者： Egger, Maximilian Bitar, Rawad Wachter-Zeh, Antonia Gündüz, Deniz Weinberger, Nir Technical University of Munich Germany Imperial College London United Kingdom Technion - Israel Institute of Technology Israel

ISBN: (纸本)9781665475549

We consider the problem of finding the channel with the highest capacity among several discrete memoryless channels (DMCs) with the same input-output alphabet sizes by means of exploration using multi-armed bandits. This setting is motivated by the problem of exploring channel statistics in communication systems by the invocation of training sequences. We particularly focus on the best arm identification problem and rank the candidate DMCs by their capacities. We propose a capacity estimator based on channel sensing and derive associated concentration results. Using this capacity estimator, we introduce BestChanID, a gap-elimination algorithm, oblivious to the capacity-achieving input distribution, which is guaranteed to output the best DMC, i.e., DMC with the largest capacity, with a desired confidence. We further introduce NaiveChanSel, an algorithm that outputs with certain confidence a DMC whose capacity is close to the largest capacity, and can be used as a subroutine in BestChanID. We analyze the sample complexity of both algorithms, i.e., the total number of channel senses, as a function of the desired confidence parameter, the number of available channels, and the input and output alphabet sizes of the channels. We show that the cost of best channel identification scales cubically with the alphabet size. © 2023 IEEE.

关键词： Computational complexity

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