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Optimising Event-Driven Spiking Neural Network with Regularisation and Cutoff

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arXiv 2023年

作者： Wu, Dengyu Jin, Gaojie Yu, Han Yi, Xinping Huang, Xiaowei Department of Computer Science University of Liverpool Liverpool United Kingdom National Mobile Communications Research Laboratory Southeast University Nanjing China State Key Laboratory of Computer Science Institute of Software CAS Beijing China Department of Electrical Engineering Chalmers University of Technology Gothenburg Sweden

Spiking neural network (SNN), as the next generation of artificial neural network (ANN), offer a closer mimicry of natural neural networks and hold promise for significant improvements in computational efficiency. However, the current SNN is trained to infer over a fixed duration, overlooking the potential of dynamic inference in SNN. In this paper, we strengthen the marriage between SNN and event-driven processing with a proposal to consider a cutoff in SNN, which can terminate SNN anytime during inference to achieve efficient inference. Two novel optimisation techniques are presented to achieve inference efficient SNN: a Top-K cutoff and a regularisation. The proposed regularisation influences the training process, optimising SNN for the cutoff, while the Top-K cutoff technique optimises the inference phase. We conduct an extensive set of experiments on multiple benchmark frame-based datasets, such as CIFAR10/100, Tiny-ImageNet, and event-based datasets, including CIFAR10-DVS, N-Caltech101 and DVS128 Gesture. The experimental results demonstrate the effectiveness of our techniques in both ANN-to-SNN conversion and direct training, enabling SNNs to require 1.76 to 2.76 × fewer timesteps for CIFAR-10, while achieving 1.64 to 1.95× fewer timesteps across all event-based datasets, with near-zero accuracy loss. These findings affirms the compatibility and potential benefits of our techniques in enhancing accuracy and reducing inference latency when integrated with existing methods. Code available: https://***/Dengyu-Wu/SNNCutoff © 2023, CC BY.

关键词： Computational efficiency

NormAUG: Normalization-guided Augmentation for Domain Generalization

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arXiv 2023年

作者： Qi, Lei Yang, Hongpeng Shi, Yinghuan Geng, Xin Ministry of Education 211189 China The School of Cyber Science and Engineering Southeast University Nanjing211189 China The State Key Laboratory for Novel Software Technology Nanjing University Nanjing210023 China The School of Computer Science and Engineering Southeast University Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications [Southeast University Ministry of Education 211189 China

Deep learning has made significant advancements in supervised learning. However, models trained in this setting often face challenges due to domain shift between training and test sets, resulting in a significant drop in performance during testing. To address this issue, several domain generalization methods have been developed to learn robust and domain-invariant features from multiple training domains that can generalize well to unseen test domains. Data augmentation plays a crucial role in achieving this goal by enhancing the diversity of the training data. In this paper, inspired by the observation that normalizing an image with different statistics generated by different batches with various domains can perturb its feature, we propose a simple yet effective method called NormAUG (Normalization-guided Augmentation). Our method includes two paths: the main path and the auxiliary (augmented) path. During training, the auxiliary path includes multiple sub-paths, each corresponding to batch normalization for a single domain or a random combination of multiple domains. This introduces diverse information at the feature level and improves the generalization of the main path. Moreover, our NormAUG method effectively reduces the existing upper boundary for generalization based on theoretical perspectives. During the test stage, we leverage an ensemble strategy to combine the predictions from the auxiliary path of our model, further boosting performance. Extensive experiments are conducted on multiple benchmark datasets to validate the effectiveness of our proposed method. Copyright © 2023, The Authors. All rights reserved.

关键词： Deep learning

Family of Mutually Uncorrelated Codes for DNA Storage Address Design

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IEEE Transactions on Nanobioscience

IEEE Transactions on Nanobioscience 2025年 PP卷 PP页

作者： Liu, Zhenlu Cao, Ben Shao, Qi Zheng, Yanfen Wang, Bin Zhou, Shihua Zheng, Pan Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian116622 China Dalian University of Technology School of Computer Science and Technology Dalian116024 China University of Canterbury Upper Riccarton Department of Accounting and Information Systems Christchurch8140 New Zealand

Deoxyribonucleic acid (DNA) has become an ideal medium for long-term storage and retrieval due to its extremely high storage density and long-term stability. But access efficiency is an existing bottleneck in DNA storage, especially the lack of high-quality random access address sequences. Therefore, in this paper, we report a series of approaches based on k-weakly mutually uncorrelated (k-WMU) codes to design the address sequence to improve the access efficiency of DNA storage. To address the problem of DNA sequences that are poorly scalable at the base level, we propose a 0-m-ruling coding scheme combined with k-WMU codes that can make address sequences avoid generating secondary structure with stem lengths ranging from 3 to 9. Based on the decoupled structure, We further extend the k-WMU codes with error correction function while satisfying combinatorial biological constraints. In order to investigate the performance of the designed address sequences for real-world applications, we perform simulation experiments based on thermodynamic properties and error correction capability as well as compared the minimum free energy (MFE), melting temperature (TM), and average decoding success rate (ADSR) with previous work. The results show that designed address sequences have a high MFE value and ADSR and a substantial reduction in TM-variance while satisfying the combinatorial biological constraints. As the quality of address sequences improves, this will help to achieve accurate random access as well as enhance the robustness of the DNA storage system. © 2002-2011 IEEE.

关键词： DNA sequences

Hybrid Digital-Analog Semantic Communications

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IEEE Journal on Selected Areas in Communications 2025年

作者： Xie, Huiqiang Qin, Zhijin Han, Zhu Letaief, Khaled B. Jinan University College of Information Science and Technology Guangzhou China Tsinghua University Department of Electronic Engineering Beijing100084 China State Key Laboratory of Space Network and Communications Beijing100084 China Beijing National Research Center for Information Science and Technology Beijing100084 China University of Houston Department of Electrical and Computer Engineering Houston United States The Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong Hong Kong

Digital and analog semantic communications (SemCom) face inherent limitations such as data security concerns in analog SemCom, as well as leveling-off and cliff-edge effects in digital SemCom. In order to overcome these challenges, we propose a novel SemCom framework and a corresponding system called HDA-DeepSC, which leverages a hybrid digitalanalog approach for multimedia transmission. This is achieved through the introduction of analog-digital allocation and fusion modules. To strike a balance between data rate and distortion, we design new loss functions that take into account long-distance dependencies in the semantic distortion constraint, essential information recovery in the channel distortion constraint, and optimal bit stream generation in the rate constraint. Additionally, we propose denoising diffusion-based signal detection techniques, which involve carefully designed variance schedules and sampling algorithms to refine transmitted signals. Through extensive numerical experiments, we will demonstrate that HDA-DeepSC exhibits robustness to channel variations and is capable of supporting various communication scenarios. Our proposed framework outperforms existing benchmarks in terms of peak signal-to-noise ratio and multi-scale structural similarity, showcasing its superiority in semantic communication quality. © 1983-2012 IEEE.

关键词： Digital communication systems

Fast Maxwell Solvers Based on Exact Discrete Eigen-Decompositions I. Two-Dimensional Case

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arXiv 2025年

作者： Wang, Lixiu Jia, Lueling Cao, Zijian Li, Huiyuan Zhang, Zhimin School of Mathematics and Physics University of Science and Technology Beijing Beijing100083 China School of Mathematics and Statistics Shandong Normal University Jinan250358 China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing101408 China State Key Laboratory of Computer Science Laboratory of Parallel Computing Institute of Software Chinese Academy of Sciences Beijing100190 China Department of Mathematics Wayne State University DetroitMI48202 United States

In this paper, we propose fast solvers for Maxwell’s equations in rectangular domains. We first discretize the simplified Maxwell’s eigenvalue problems by employing the lowest-order rectangular Nédélec elements and derive the discrete eigen-solutions explicitly, providing a Hodge-Helmholtz decomposition framework at the discrete level. Based on exact eigen-decompositions, we further design fast solvers for various Maxwell’s source problems, guaranteeing either the divergence-free constraint or the Gauss’s law at the discrete level. With the help of fast sine/cosine transforms, the computational time grows asymptotically as O(n2 log n) with n being the number of grids in each direction. Our fast Maxwell solvers outperform other existing Maxwell solvers in the literature and fully rival fast scalar Poisson/Helmholtz solvers based on trigonometric transforms in either efficiency, robustness, or storage complexity. It is also utilized to perform an efficient pre-conditioning for solving Maxwell’s source problems with variable coefficients. Finally, numerical experiments are carried out to illustrate the effectiveness and efficiency of the proposed fast *** Codes 65N30, 35Q61, 65F05, 68W40 © 2025, CC BY.

关键词： Maxwell equations

UniGPS: A unified programming framework for distributed graph processing

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arXiv 2021年

作者： Wang, Zhaokang Li, Junhong Qi, Yifan Zhu, Guanghui Yuan, Chunfeng Huang, Yihua State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Department of Computer Science and Technology Nanjing University Nanjing China

The industry and academia have proposed many distributed graph processing systems. However, the existing systems are not friendly enough for users like data analysts and algorithm engineers. On the one hand, the programing models and interfaces differ a lot in the existing systems, leading to high learning costs and program migration costs. On the other hand, these graph processing systems are tightly bound to the underlying distributed computing platforms, requiring users to be familiar with distributed computing. To improve the usability of distributed graph processing, we propose a unified distributed graph programming framework UniGPS. Firstly, we propose a unified cross-platform graph programming model VCProg for UniGPS. VCProg hides details of distributed computing from users. It is compatible with the popular graph programming models Pregel, GAS, and Push-Pull. VCProg programs can be executed by compatible distributed graph processing systems without modification, reducing the learning overheads of users. Secondly, UniGPS supports Python as the programming language. We propose an interprocess-communication-based execution environment isolation mechanism to enable Java/C++based systems to call user-defined methods written in Python. The experimental results show that UniGPS enables users to process big graphs beyond the memory capacity of a single machine without sacrificing usability. UniGPS shows near-linear data scalability and machine scalability. Copyright © 2021, The Authors. All rights reserved.

关键词： Python

Controlled Quantum Network Coding Without Loss of Information

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computers, Materials & Continua 2021年第12期69卷 3967-3979页

作者： Xiu-Bo Pan Xiu-Bo Chen Gang Xu Haseeb Ahmad Tao Shang Zong-Peng Li Yi-Xian Yang Information Security Center State Key Laboratory of Networking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijing100876China School of Information Science and Technology North China University of TechnologyBeijing100144China Department of Computer Science National Textile University Faisalabad37610Pakistan School of Cyber Science and Technology Beihang UniversityBeijing100083China Huawei Technologies Co.Ltd. Shenzhen518129China School of Computer Science Wuhan UniversityWuhan430072China

Quantum network coding is used to solve the congestion problem in quantum communication,which will promote the transmission efficiency of quantum information and the total throughput of quantum *** propose a novel controlled quantum network coding without information *** effective transmission of quantum states on the butterfly network requires the consent form a third-party controller ***,two pairs of threeparticle non-maximum entangled states are pre-shared between senders and *** adding auxiliary particles and local operations,the senders can predict whether a certain quantum state can be successfully transmitted within the butterfly network based on the Z-{10>,|1>}***,when trans-mission fails upon prediction,the quantum state will not be lost,and it will sill be held by the ***,the controller Charlie re-prepares another three-particle non-maximum entangled state to start a new *** the predicted transmission is successful,the quantum state can be transmitted successfully within the butterfly *** the receiver wants to receive the effective quantum state,the quantum measurements from Charlie are ***,when the transmission fails,Charlie does not need to integrate the X-{1+>,1->}basis to measure its own particles,by which quantum resources are *** not only controls the effective transmission of quantum states,but also the usage of classical and quantum ***,the implementation of the quantum circuits,as well as a flow chart and safety analysis of our scheme,is proposed.

关键词： Controlled quantum network coding without information loss quantum teleportation perfect transmission

DPA-2:a large atomic model as a multitask learner

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npj Computational Materials 2024年第1期10卷 185-199页

作者： Duo Zhang Xinzijian Liu Xiangyu Zhang Chengqian Zhang Chun Cai Hangrui Bi Yiming Du Xuejian Qin Anyang Peng Jiameng Huang Bowen Li Yifan Shan Jinzhe Zeng Yuzhi Zhang Siyuan Liu Yifan Li Junhan Chang Xinyan Wang Shuo Zhou Jianchuan Liu Xiaoshan Luo Zhenyu Wang Wanrun Jiang Jing Wu Yudi Yang Jiyuan Yang Manyi Yang Fu-Qiang Gong Linshuang Zhang Mengchao Shi Fu-Zhi Dai Darrin M.York Shi Liu Tong Zhu Zhicheng Zhong Jian Lv Jun Cheng Weile Jia Mohan Chen Guolin Ke Weinan E Linfeng Zhang Han Wang AI for Science Institute BeijingP.R.China DP Technology BeijingP.R.China Academy for Advanced Interdisciplinary Studies Peking UniversityBeijingP.R.China State Key Lab of Processors Institute of Computing TechnologyChinese Academy of SciencesBeijingP.R.China University of Chinese Academy of Sciences BeijingP.R.China HEDPS CAPTCollege of EngineeringPeking UniversityBeijingP.R.China Ningbo Institute of Materials Technology and Engineering Chinese Academy of SciencesNingboP.R.China CAS Key Laboratory of Magnetic Materials and Devices and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology Chinese Academy of SciencesNingboP.R.China School of Electronics Engineering and Computer Science Peking UniversityBeijingP.R.China Shanghai Engineering Research Center of Molecular Therapeutics&New Drug Development School of Chemistry and Molecular EngineeringEast China Normal UniversityShanghaiP.R.China Laboratory for Biomolecular Simulation Research Institute for Quantitative Biomedicine and Department of Chemistry and Chemical BiologyRutgers UniversityPiscatawayNJUSA Department of Chemistry Princeton UniversityPrincetonNJUSA College of Chemistry and Molecular Engineering Peking UniversityBeijingP.R.China Yuanpei College Peking UniversityBeijingP.R.China School of Electrical Engineering and Electronic Information Xihua UniversityChengduP.R.China State Key Laboratory of Superhard Materials College of PhysicsJilin UniversityChangchunP.R.China Key Laboratory of Material Simulation Methods&Software of Ministry of Education College of PhysicsJilin UniversityChangchunP.R.China International Center of Future Science Jilin UniversityChangchunP.R.China Key Laboratory for Quantum Materialsof Zhejiang Province Department of PhysicsSchool of ScienceWestlake UniversityHangzhouP.R.China Atomistic Simulations Italian Institute of TechnologyGenovaItaly State Key Laboratory of Physical Chemistry of Solid Surface iChEMCollege of Chemistry and Chemical EngineeringXiame

The rapid advancements in artificial intelligence(AI)are catalyzing transformative changes in atomic modeling,simulation,and ***-driven potential energy models havedemonstrated the capability to conduct large-scale,long-duration simulations with the accuracy of ab initio electronic structure ***,the model generation process remains a bottleneck for large-scale *** propose a shift towards a model-centric ecosystem,wherein a large atomic model(LAM),pretrained across multiple disciplines,can be efficiently fine-tuned and distilled for various downstream tasks,thereby establishing a new framework for molecular *** this study,we introduce the DPA-2 architecture as a prototype for ***-trained on a diverse array of chemical and materials systemsusing a multi-task approach,DPA-2demonstrates superior generalization capabilities across multiple downstream tasks compared to the traditional single-task pre-training and fine-tuning *** approach sets the stage for the development and broad application of LAMs in molecular and materials simulation research.

关键词： DPA establishing thereby

DFCM: A Distributed Floor Control Mechanism in PoC

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Chinese Journal of Electronics 2023年第4期20卷 739-746页

作者： LIAO Jianxin LIU Haipeng LI Tonghong WANG Jingyu ZHU Xiaomin State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China EBUPT Information Technology Co. Ltd. Beijing China Department of Computer Science Technical University of Madrid Spain

With the fast progress of Collaborative multimedia application (CMA) running on overlay network, Push to talk over cellular (PoC) attracts significant interest in the field of mobile cellular communications. PoC is an on-demand, resource efficient, half-duplex multimedia service. Due to the half-duplex nature, only one user is allowed to speak at a time, and the others listen. If listeners want to speak, they have to contend for the right to speak and wait for the permission if request waiting is supported. Open mobile alliance (OMA) proposed a centralized controlling based floor control mechanism for speak right coordination in PoC, which is called Talk burst control protocol (TBCP). But it has many limitations in scalability, reliability and robustness as all centralized approaches have. In addition, none of available distributed approaches well meets mobile users' requirements in PoC, especially for the request waiting function. In this paper we put forward a novel distributed floor control mechanism with request waiting for PoC, which is called Distributed floor control mechanism (DFCM). From the performance evaluation of DFCM and TBCP, we find that DFCM outperforms TBCP especially when performance of the central node, Controlling server (CS), drops down due to heavy load. Finally, this paper is summarized and future work is forecasted.

关键词： Performance evaluation Protocols Overlay networks Scalability Half-duplex system Collaboration Robustness