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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Huihuan Xu Siqi Zhang Jingkun Yue Tong Tong Xiaohong Liu Guangyu Wang State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China China Mobile Information Technology Center Beijing China UCL Cancer Institute University College London London United Kingdom

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

The Segment Anything Model (SAM) has recently gained popularity in the filed of 3D medical segmentation for its remarkable generalization capability. However, most SAM-based 2D to 3D adaptation methods requires prompting each slice in a medical volume, which is label-consuming. How to effectively propagate the prompts on the single slice to all slices while ensuring the continuity of the entire volume boundaries is still an unresolved challenge. To address this, we propose Adjacent-Slice Correspondence-guided 3D SAM(ASC-3DSAM), a novel approach for 3D medical segmentation, which matches key points or features between adjacent slices to establish correspondences for neighboring slices, thereby propagating prompt information to the entire volume using just a single prompted slice. Specifically, we present a Slice-Correlation Module (SCM), the adjacent slice as the query is segmented using the mask information from the central slice, thereby propagating prompt information to the entire volume. In addition, a hybrid continuity loss called Continuous Boundary-aware Loss(CBL) is proposed, which takes the form of a distance metric on the space of contours and integrates gradient information of the volume boundaries to supervise the continuity of the entire volume. Our approach is evaluated on two public datasets, including AMOS and BTCV. Experimental results demonstrate that ASC-3DSAM achieves state-of-the-art (SOTA) performance, with an improvement of approximately 1.86% of Dice and 1.92(mm) of HD95 compared to the next-best method. Furthermore, our method can produce smooth closed boundaries of the entire volumes outperforming the SOTA models.

关键词： Measurement Image segmentation Solid modeling Adaptation models Three-dimensional displays Shape Biological system modeling approximation algorithms Bioinformatics Biomedical imaging

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On Approximability of Satisfiable k-CSPs: V

arXiv

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arXiv 2024年

作者： Bhangale, Amey Khot, Subhash Minzer, Dor Department of Computer Science and Engineering University of California Riverside United States Department of Computer Science Courant Institute of Mathematical Sciences New York University United States Department of Mathematics Massachusetts Institute of Technology United States

We propose a framework of algorithm vs. hardness for all Max-CSPs and demonstrate it for a large class of predicates. This framework extends the work of Raghavendra [STOC, 2008], who showed a similar result for almost satisfiable Max-CSPs. Our framework is based on a new hybrid approximation algorithm, which uses a combination of the Gaussian elimination technique (i.e., solving a system of linear equations over an Abelian group) and the semidefinite programming relaxation. We complement our algorithm with a matching dictator vs. quasirandom test that has perfect completeness. The analysis of our dictator vs. quasirandom test is based on a novel invariance principle, which we call the mixed invariance principle. Our mixed invariance principle is an extension of the invariance principle of Mossel, O’Donnell and Oleszkiewicz [Annals of Mathematics, 2010] which plays a crucial role in Raghavendra’s work. The mixed invariance principle allows one to relate 3-wise correlations over discrete probability spaces with expectations over spaces that are a mixture of Guassian spaces and Abelian groups, and may be of independent interest. © 2024, CC BY.

关键词： approximation algorithms

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Optimality of Meta-Converse for Channel Simulation

Optimality of Meta-Converse for Channel Simulation

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IEEE International Symposium on Information Theory

作者： Mario Berta Omar Fawzi Aadil Oufkir Institute for Quantum Information RWTH Aachen University Aachen Germany Univ Lyon Inria ENS Lyon UCBL LIP. Lyon France

ISBN: (数字)9798350382846

ISBN: (纸本)9798350382853

We study the effect of shared non-signaling correlations for the problem of simulating a channel using noiseless communication in the one-shot setting. For classical channels, we show how to round any non-signaling-assisted simulation strategy - which exactly corresponds to the meta-converse for channel simulation - to a strategy that only uses shared randomness. For quantum channels, we round any non-signaling-assisted simulation strategy to a strategy that only uses shared entanglement. As our main result, we prove a guarantee on the ratio of success probabilities of at least $(1-\frac{-1}{\mathbf{e}})$ , for both the classical and the quantum setting. We further - show this ratio to be optimal. It can be improved to $(1-\frac{1}{t})$ using $o$ (ln $(t)$ ) additional bits (qubits) of communication.

关键词： Correlation Quantum channels Qubit approximation algorithms Information theory

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MPC-based Rate Calculation for Effective Bandwidth in 5G Communication Systems

MPC-based Rate Calculation for Effective Bandwidth in 5G Com...

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Communication Systems (ECCS), European Conference on

作者： Jun Liu Paulo Renato Da Costa Mendes Andreas Wirsen Daniel Görges Department of System Analysis Prognosis and Control Fraunhofer Institute for Industrial Mathematics (ITWM) University of Kaiserslautern-Landau Kaiserslautern Germany Department of System Analysis Prognosis and Control Fraunhofer Institute for Industrial Mathematics (ITWM) Kaiserslautern Germany Institute of Electromobility University of Kaiserslautern-Landau Kaiserslautern Germany

ISBN: (数字)9798350377927

ISBN: (纸本)9798350377934

The effective bandwidth plays an important role in different aspects of nowadays communication systems. The concept is based on calculating a constant transmission data rate for certain incoming traffic distribution in an asymptotic manner. Meanwhile, the latency and reliability of the users are jointly considered and satisfied. The effective bandwidth is therefore widely used to simplify the analysis of a variety of 5 G communication tasks (e.g. resource allocation for ultra-reliable low-latency communication). Nevertheless, the concept is difficult to extend to traffic patterns other than Poisson distribution. Moreover, the performance of effective bandwidth can hardly guarantee the rate to be tight upper-bound of the incoming traffic when the user’s delay requirement is extremely small. In this work, we consider the effective bandwidth concept in a finite time horizon with a given traffic prediction module. The output rate calculation is simplified and updated according to the model predictive control (MPC) concept. We further study the influence of the length of the time horizon and summarize that our proposed algorithm approximately equals the effective bandwidth concept when having an infinite time horizon. Moreover, a practical calculation method for Poisson distributed incoming traffic is provided and compared with the effective bandwidth concept. The simulation results indicate that the MPC-based solution can provide similar rates to effective bandwidth in both stationary and dynamic traffic scenarios. Meanwhile, the introduced method can reduce resource waste and improve the efficiency of the system. For Poisson-distributed incoming traffic, the optimal MPC time horizon can be easily calculated. With the obtained time horizon, a more accurate data rate to the reference value can be calculated than effective bandwidth.

关键词： 5G mobile communication Simulation Bandwidth Quality of service Ultra reliable low latency communication Traffic control Prediction algorithms approximation algorithms Resource management Reliability

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Exact Sampling of Spanning Trees via Fast-forwarded Random Walks

arXiv

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arXiv 2024年

作者： Tam, Edric Dunson, David B. Duan, Leo L. Department of Statistical Science Duke University Box 90251 DurhamNC27708 United States Department of Statistical Science Department of Mathematics Duke University Box 90251 DurhamNC27708 United States Department of Statistics University of Florida 101C Griffin-Floyd Hall P.O. Box 118545 GainesvilleFL32611 United States

Tree graphs are routinely used in statistics. When estimating a Bayesian model with a tree component, sampling the posterior remains a core difficulty. Existing Markov chain Monte Carlo methods tend to rely on local moves, often leading to poor mixing. A promising approach is to instead directly sample spanning trees on an auxiliary graph. Current spanning tree samplers, such as the celebrated Aldous–Broder algorithm, predominantly rely on simulating random walks that are required to visit all the nodes of the graph. Such algorithms are prone to getting stuck in certain sub-graphs. We formalize this phenomenon using the bottlenecks in the random walk’s transition probability matrix. We then propose a novel fast-forwarded cover algorithm that can break free from bottlenecks. The core idea is a marginalization argument that leads to a closed-form expression which allows for fast-forwarding to the event of visiting a new node. Unlike many existing approximation algorithms, our algorithm yields exact samples. We demonstrate the enhanced efficiency of the fast-forwarded cover algorithm, and illustrate its application in fitting a Bayesian dendrogram model on a Massachusetts crimes and communities dataset. © 2024, CC BY.

关键词： approximation algorithms

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Influence Distribution for Misinformation Containment Under Competitive Activation Models

Influence Distribution for Misinformation Containment Under ...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Ming Gu Wei-Neng Chen Xiao-Min Hu Sang-Woon Jeon School of Computer Science and Engineering South China University of Technology Guangzhou China Department of Electrical and Electronic Engineering Hanyang University Ansan South Korea

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

The widespread adoption of social networks facilitates the dissemination of authentic information while also accelerating the spread of misinformation, such as rumors. The propagation of positive information can enhance user awareness and mitigate the hazards of misinformation. The misinformation containment (MC) problem aims to identify a set o $k$ nodes that initiate the spread of positive information, maximizing its influence while minimizing the hazards of misinformation. The greedy approach, which employs extensive Monte Carlo simulations to estimate influence, is time-consuming and can only prioritize either propagation or containment, but not both. This paper studies the MC problem under competitive activation models. Based on geometric models of probability, we calculate the approximate probabilities of nodes being activated by positive information and misinformation at various times. Taking into account the two-hop theory, we propose a consistent and efficient computational method to assess node influence distribution from the perspectives of propagation and containment. This method strikes a balance between propagation and containment, surpassing degree centrality, further informing a heuristic solution to the MC problem. The heuristic solution's overall performance surpasses that of greedy approaches, which can only prioritize one aspect. Experiments on real-world networks demonstrate that our approach effectively balances the propagation of positive information and misinformation containment with low time complexity.

关键词： Measurement Monte Carlo methods Social networking (online) Computational modeling Geometric modeling Probability approximation algorithms Hazards Fake news Time complexity

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DC Optimal Power Flow in Unit Commitment Using Quantum Computing: An ADMM Approach

DC Optimal Power Flow in Unit Commitment Using Quantum Compu...

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Annual North-American Power Symposium

作者： Madan Rana Magar Dilip Pandit Duong Nguyen Nga Nguyen Electrical Engineering and Computer Science University of Wyoming Laramie WY

ISBN: (数字)9798331521035

ISBN: (纸本)9798331521042

This paper introduces an approach to solve unit commitment-based DC optimal power flow using the quantum-based alternating direction method of multipliers optimizer. The substantial interconnection of current generation and loads and the widespread incorporation of renewable energy have significantly altered and increased the complexity of the grid. As a result, efficient planning and operation of the power grid have become central focuses. This paper proposes an advanced method to solve DC-optimal power flow via quantum heuristic approaches leveraging the power of both quantum and classical computing. This is achieved by splitting the procedure to decompose a mixed binary quadratic problem into a quadratic unconstrained binary optimization sub-problem which is solved using a quantum approximate optimization algorithm. Following this, a continuous convex-constrained sub-problem is solved with a classical optimization solver. Within the DC-OPF, the startup cost and shutdown cost of each generator are incorporated in addition to the general cost function with the generator's cost coefficients. The DC-OPF is solved using the IBM Qiskit software development kit on an IEEE-14 bus system. The results obtained are then validated with the results obtained from classical methods using MATPOWER.

关键词： Renewable energy sources Quantum computing Costs Software algorithms approximation algorithms Generators Planning Optimization Load flow Software development management

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The Competition Complexity of Prophet Inequalities

arXiv

引用

arXiv 2024年

作者： Brustle, Johannes Correa, José Dutting, Paul Ezra, Tomer Feldman, Michal Verdugo, Victor London School of Economics United Kingdom Universidad de Chile Santiago Chile Google Research Zurich Switzerland Harvard University Cambridge United States Tel Aviv University Israel Microsoft ILDC Universidad de O'Higgins Rancagua Chile

We study the classic single-choice prophet inequality problem through a resource augmentation lens. Our goal is to bound the (1-ϵ)-competition complexity of different types of online algorithms. This metric asks for the smallest k such that the expected value of the online algorithm on k copies of the original instance, is at least a (1 - ϵ)-approximation to the expected offline optimum on a single copy. We show that block threshold algorithms, which set one threshold per copy, are optimal and give a tight bound of k = Θ(log log 1/ϵ). This shows that block threshold algorithms approach the offline optimum doubly-exponentially fast. For single threshold algorithms, we give a tight bound of k = Theta;(log 1/ϵ), establishing an exponential gap between block threshold algorithms and single threshold algorithms. Our model and results pave the way for exploring resource-augmented prophet inequalities in combinatorial settings. In line with this, we present preliminary findings for bipartite matching with one-sided vertex arrivals, as well as in XOS combinatorial auctions. Our results have a natural competition complexity interpretation in mechanism design and pricing *** Codes 90C59, 68W27, 62L15, 60G40 Copyright © 2024, The Authors. All rights reserved.

关键词： approximation algorithms

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Approximate String Matching Algorithm Using Multiple-Character Inverted Lists

Approximate String Matching Algorithm Using Multiple-Charact...

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Research, Invention, and Innovation Congress (RI2C)

作者： Soontaree Thumsuwan Nuanprang Sangurai Chouvalit Khancome Department of Information Technology Faculty of Science and Technology Rajabhat Rajanagarindra University Chachoengsao Thailand Department of Computer Science Faculty of Science Ramkhamhaeng University Bangkok Thailand

ISBN: (数字)9798331506018

ISBN: (纸本)9798331506025

Approximate string matching algorithms, which permit mismatched characters, are extensively employed in software featuring search tools, database management systems, and various applications and online services. Consequently, the development of new algorithms to facilitate faster and more accurate searches continues to pose a significant challenge for researchers. This research article introduces a novel approximate string matching algorithm, designated as m-IVLASM, derived from the Multiple-Character Inverted Lists data structure traditionally utilized for single pattern string matching. The proposed algorithm exhibits flexibility by allowing adjustable search parameters for each query, thereby enhancing search speed and efficiency compared to conventional methods. Operating in linear time, the algorithm demonstrates superior performance. Experimental results, derived from both random data and real-world datasets, provide compelling evidence that the new method significantly surpasses previous approaches in terms of effectiveness. The optimal efficiency for character length factor splitting was identified at values of 0.5 and 0.8.

关键词： Technological innovation Accuracy Software algorithms approximation algorithms Data structures Software Database systems Pattern matching

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Fairness and Incentive Compatibility via Percentage Fees

arXiv

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arXiv 2024年

作者： Dobzinski, Shahar Oren, Sigal Vondrák, Jan Weizmann Institute of Science Ben Gurion University of the Negev Stanford University United States

We study incentive-compatible mechanisms that maximize the Nash Social Welfare. Since traditional incentive-compatible mechanisms cannot maximize the Nash Social Welfare even approximately, we propose changing the traditional model. Inspired by a widely used charging method (e.g., royalties, a lawyer that charges some percentage of possible future compensation), we suggest charging the players some percentage of their value of the outcome. We call this model the percentage fee model. We show that there is a mechanism that maximizes exactly the Nash Social Welfare in every setting with non-negative valuations. Moreover, we prove an analog of Roberts theorem that essentially says that if the valuations are non-negative, then the only implementable social choice functions are those that maximize weighted variants of the Nash Social Welfare. We develop polynomial time incentive compatible approximation algorithms for the Nash Social Welfare with subadditive valuations and prove some hardness results. Copyright © 2024, The Authors. All rights reserved.

关键词： approximation algorithms

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