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2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

作者： Zhou, Guokai Chen, Weiting East China Normal University MOE Research Center of Software/Hardware Co-Design Engineering Shanghai Key Laboratory of Trustworthy Computing Shanghai China

ISBN: (纸本)9781665468190

Next-generation sequencing technologies generated a large number of new sequenced proteins. Classifying these proteins into functional families is an important task in the field of biological protein property research. The high-cost and time-consuming drawbacks of bioassays promote the development of machine learning-based protein classification studies. However, previous work only used single level features, which were not informative enough and had classification bias. In this paper, we propose a new model named PCNM to alleviate the above problems. Different from previous work that extracts only a single level of features, the PCNM model uses a Convolutional Neural Network (CNN) module and a Global and Local feature (GL) module to extract feature at three levels: conserved domains, amino acids, and protein sequences. The experimental results of the Phages of orthologous groups dataset (POG) and the G-protein coupled receptor superfamily dataset (GPCR) show that our proposed PCNM outperforms currently available methods in five metrics: accuracy, precision, recall, F1 score, and MCC. PCNM achieves a high accuracy of 85.12% on the GPCR sub-subfamily dataset and 81.42% on the POG dataset. The robustness experiments of PCNM further demonstrate that the model alleviates the classification bias. © 2022 IEEE.

关键词： Proteins

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An Adaptive Proximal Inexact Gradient Framework and Its Application to Per-Antenna Constrained Joint Beamforming and Compression Design

arXiv

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arXiv 2025年

作者： Fan, Xilai Jiang, Bo Liu, Ya-Feng State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Ministry of Education Key Laboratory of NSLSCS School of Mathematical Sciences Nanjing Normal University Nanjing210023 China

In this paper, we propose an adaptive proximal inexact gradient (APIG) framework for solving a class of nonsmooth composite optimization problems involving function and gradient errors. Unlike existing inexact proximal gradient methods, the proposed framework introduces a new line search condition that jointly adapts to function and gradient errors, enabling adaptive stepsize selection while maintaining theoretical guarantees. Specifically, we prove that the proposed framework achieves an ϵ-stationary point within O(ϵ−2) iterations for nonconvex objectives and an ϵ-optimal solution within O(ϵ−1) iterations for convex cases, matching the best-known complexity in this context. We then custom-apply the APIG framework to an important signal processing problem: the joint beamforming and compression problem (JBCP) with per-antenna power constraints (PAPCs) in cooperative cellular networks. This customized application requires careful exploitation of the problem’s special structure such as the tightness of the semidefinite relaxation (SDR) and the differentiability of the dual. Numerical experiments demonstrate the superior performance of our custom-application over state-of-the-art benchmarks for the JBCP. © 2025, CC BY.

关键词： Beamforming

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Memristive structure of Nb/HfOx/Pd with controllable switching mechanisms to perform featured actions in neuromorphic networks

引用

Nano Research 2022年第9期15卷 8410-8418页

作者： Junwei Yu Fei Zeng Qin Wan Yiming Sun Leilei Qiao Tongjin Chen Huaqiang Wu Zhen Zhao Jiangli Cao Feng Pan Key Laboratory of Advanced Materials(MOE) School of Materials Science and EngineeringTsinghua UniversityBeijing 100084China Center for Brain Inspired Computing Research(CBICR) Tsinghua UniversityBeijing 100084China Microelectronics Institute Tsinghua UniversityBeijing 100084China School of Materials Science and Engineering University of Science and Technology BeijingBeijing 100083China

All memristor neuromorphic networks have great potential and advantage in both technology and computational protocols for artificial *** is crucial to find suitable elementary units for both performing featured neuromorphic functions and fabrication in large *** a simple memristive structure,Nb/HfOx/Pd,is proposed for this *** two resistive switching mechanisms,Mott transition of NbO2 and oxygen vacancy(Vo)migration,can be controlled by modulating external bias *** bias activates reversible phase transition and restrains Vo filament formation to allow the memristor to mimic the firing action *** bias activates Vo filament formation and restrains the other to allow the memristor to mimic synaptic plasticity and learning *** system can respond adaptively to naturally generated action potentials and modified synaptic signals from the same memristive *** addition,some special features related to signal encoding and recognition are discovered when the system is settled according to chaos circuit *** study provides a novel approach for designing elementary units for neuromorphic computations.

关键词： memristive system phase transition oxygen vacancy action potential synaptic plasticity

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Desingularization of bounded-rank tensor sets

arXiv

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arXiv 2024年

作者： Gao, Bin Peng, Renfeng Yuan, Ya-Xiang State Key Laboratory of Scientific and Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China State Key Laboratory of Scientific and Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China

Low-rank tensors appear to be prosperous in many applications. However, the sets of bounded-rank tensors are non-smooth and non-convex algebraic varieties, rendering the low-rank optimization problems to be challenging. To this end, we delve into the geometry of bounded-rank tensor sets, including Tucker and tensor train formats. We propose a desingularization approach for bounded-rank tensor sets by introducing slack variables, resulting in a low-dimensional smooth manifold embedded in a higher-dimensional space while preserving the structure of low-rank tensor formats. Subsequently, optimization on tensor varieties can be reformulated to optimization on smooth manifolds, where the methods and convergence are well explored. We reveal the relationship between the landscape of optimization on varieties and that of optimization on manifolds. Numerical experiments on tensor completion illustrate that the proposed methods are in favor of others under different rank *** Codes 15A69, 65K05, 65F30, 90C30 Copyright © 2024, The Authors. All rights reserved.

关键词： Tensors

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Geometric Contrastive Learning for Heterogeneous Graphs Encoding

Geometric Contrastive Learning for Heterogeneous Graphs Enco...

引用

2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Wang, Siheng Cao, Guitao Wu, Chunwei East China Normal University Shanghai Key Laboratory of Trustworthy Computing Shanghai200062 China MoE Engineering Research Center of SW/HW Co-design Technology and Application East China Normal University Shanghai200062 China

ISBN: (纸本)9798350337020

Heterogeneous graphs can represent many network structures in the real world, and research on heterogeneous graph data has attracted more attention. Most existing approaches require additional label information to obtain meaningful node representations. However, labeling heterogeneous graphs is tedious and time-consuming, and low-quality labels will harm the efficiency of models. In addition, the number of nodes increases exponentially with the distance from the root node, but the linearly expanding Euclidean space is difficult to match this growth rate. In this paper, we propose a unified framework that leverages the label irrelevance of contrastive learning and the unique expressive ability of hyperbolic space to encode heterogeneous graphs. Specifically, we use the contrast mechanism to obtain semantic information in an unsupervised way. Meanwhile, we design hyperbolic encoders that are more suitable for graph structure to learn the latent information from heterogeneous graphs efficiently. Experiments on four real-world heterogeneous graph data sets demonstrate the competitive efficacy of the proposed method. © 2023 IEEE.

关键词： contrastive learning geometric learning heterogeneous graphs

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Buffer with Feature Tokens: Combating Confusion in Medical Image Continual Learning

Buffer with Feature Tokens: Combating Confusion in Medical I...

引用

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Zheming Fan Weiting Chen Jiahao Fan Ruizhi Yu Shanghai Key Laboratory of Trustworthy Computing MOE Research Center of Software/Hardware Co-Design Engineering East China Normal University

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Due to its complexity and privacy concerns, medical data is often difficult to collect fully at once. New data emerges with the discovery of new diseases and advances in medical technology, but privacy concerns limit its storage. When deep learning models require training on datasets of new diseases, they often suffer from catastrophic forgetting, where the models’ performance on previously learned data degrades significantly. Recently, pre-trained continual learning methods have been proposed. Unlike earlier continual learning methods, these new approaches do not require learning excessive amounts of new knowledge, furthermore, they can still achieve good performance even when the pre-trained feature extractor is completely frozen. For these approaches, the performance degradation is not primarily due to catastrophic forgetting, but rather confusion. To combat confusion, we propose a method using a buffer with feature tokens (BWFT) which is cheaper and safer than directly storing the original data. Additionally, we propose a feature merge method to further reduce storage and computation costs. In the class-incremental scenario, our method outperforms state-of-the-art methods on multiple medical datasets as well as natural image datasets. Code is available at https://***/1345475677/BWFT.

关键词： Continuing education Degradation Training Data privacy Privacy Costs Feature extraction Data models Biomedical imaging Diseases

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Taking Myopic Best Response Against the Hedge Algorithm 42

Taking Myopic Best Response Against the Hedge Algorithm

引用

42nd Chinese Control Conference, CCC 2023

作者： Guo, Xinxiang Mu, Yifen School of Mathematical Sciences University of Chinese Academy of Sciences Beijing China Academy of Mathematics and Systems Science The State Key Laboratory of Scientific and Engineering Computing Chinese Academy of Sciences Beijing China Academy of Mathematics and Systems Science The Key Laboratory of Systems and Control Chinese Academy of Sciences Beijing China

ISBN: (纸本)9789887581543

With the rapid development of artificial intelligence (AI), the game between the human and machine/AI becomes more and more common. The related theoretical analysis becomes significant and necessary, which however is still rare. This problem involves evolution analysis and optimal control of dynamic game systems driven by learning algorithms. In this paper, we consider a finitely repeated two-player zero-sum game. We study the dynamic evolution process of the game system, in which one player employs the Hedge algorithm and the other player takes the myopic best response. By the updating formula of the Hedge algorithm, we define a quantity called the state and construct the State Transition Triangle Graph (STTG). Then, we prove that the game system is periodic after o(T) stages. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Artificial intelligence

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The superiority of nonconjugated structures in fluorescence:through-space ***-bond charge transfer

引用

Science China Chemistry 2024年第9期67卷 3121-3130页

作者： Weihao Tu Zuping Xiong Lei Wang Jianyu Zhang Jing Zhi Sun Haoke Zhang Ben Zhong Tang MOE Key Laboratory of Macromolecular Synthesis and Functionalization Department of Polymer Science and EngineeringZhejiang UniversityHangzhou 310058China Zhejiang-Israel Joint Laboratory of Self-Assembling Functional Materials ZJU-Hangzhou Global Scientific and Technological Innovation CenterZhejiang UniversityHangzhou 311215China Centre of Healthcare Materials Shaoxing InstituteZhejiang UniversityShaoxing 312000China Department of Chemistry Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and ReconstructionThe Hong Kong University of Science and TechnologyHong Kong 999077China School of Science and Engineering Shenzhen Institute of Aggregate Science and TechnologyThe Chinese University of Hong KongShenzhen(CUHK-Shenzhen)Guangzhou 518172China

Constructing charge transfer(CT)state by introducing donor(D)and acceptor(A)is an efficient strategy to regulate the photophysical properties of luminescent *** CT-type luminophores are built onπ-conjugated fused-ring structures,which always show hybrid CT/locally excited(LE)states and luminescence quenching effect in the aggregate *** this work,eight conjugated biphenyl(BP)and nonconjugated diphenylmethane(DPM)derivatives with different donors and acceptors are synthesized to investigate the CT *** photophysical characterization and theoretical calculation demonstrate that the through-space CT(TSCT)in nonconjugated DA-DPM exhibit superior photophysical performance than the conjugated DA-BP with through-bond CT(TBCT),the main manifestations are as follows:(1)TSCT luminophores produce longer maximum emission wavelength(λ_(em))than the corresponding TBCT *** example,the longest λ_(em)of DMA-CN-DPM(DMA,dimethylamino)is 621 nm but the corresponding λ_(em)of DMA-CN-BP is only 480 nm.(2)TSCT-based DA-DPM demonstrates more sensitive responsiveness to environmental stimuli such as temperature and polarity.(3)Complete separation of the the highest occupied molecular orbital(HOMO)and the lowest unoccupied molecular orbital(LUMO)distribution exists in all kinds of conformation of DA-DPM,which was hard to realize in conjugated DA-BP.

关键词： through-space charge transfer through-space conjugation clusteroluminescence diphenylmethane

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Flexible Large-Area Graphene Films of 50-600 nm Thickness with High Carrier Mobility

引用

Nano-Micro Letters 2023年第9期15卷 1-14页

作者： Shiyu Luo Li Peng Yangsu Xie Xiaoxue Cao Xiao Wang Xiaoting Liu Tingting Chen Zhanpo Han Peidong Fan Haiyan Sun Ying Shen Fan Guo Yuxing Xia Kaiwen Li Xin Ming Chao Gao MOE Key Laboratory of Macromolecular Synthesis and Functionalization Department of Polymer Science and EngineeringZhejiang UniversityHangzhou 310027People’s Republic of China School of Micro-Nanoelectronics Zhejiang UniversityZJU-Hangzhou Global Scientific and Technological Innovation CenterHangzhou 311200People’s Republic of China College of Chemistry and Environmental Engineering Shenzhen UniversityShenzhen 518055GuangdongPeople’s Republic of China Shenzhen Key Laboratory of Nanobiomechanics Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055People’s Republic of China Hangzhou Gaoxi Technol Co Ltd Hangzhou 311113People’s Republic of China

Bulk graphene nanofilms feature fast electronic and phonon transport in combination with strong light-matter interaction and thus have great potential for versatile applications,spanning from photonic,electronic,and optoelectronic devices to charge-stripping and electromagnetic shielding,***,large-area flexible close-stacked graphene nanofilms with a wide thickness range have yet to be ***,we report a polyacrylonitrile-assisted’substrate replacement’strategy to fabricate large-area free-standing graphene oxide/polyacrylonitrile nanofilms(lateral size~20 cm).Linear polyacrylonitrile chains-derived nanochannels promote the escape of gases and enable macro-assembled graphene nanofilms(nMAGs)of 50-600 nm thickness following heat treatment at 3,000℃.The uniform nMAGs exhibit 802-1,540 cm^(2)V-1s-1carrier mobility,4.3-4.7 ps carrier lifetime,and>1,581 W m^(-1)K^(-1)thermal conductivity(n MAG-assembled 10μm-thick films,mMAGs).nMAGs are highly flexible and show no structure damage even after 1.0×10^(5)cycles of ***,n MAGs broaden the detection region of graphene/silicon heterojunction from near-infrared to mid-infrared and demonstrate higher absolute electromagnetic interference(EMI)shielding effectiveness than state-of-the-art EMI materials of the same *** results are expected to lead to the broad applications of such bulk nanofilms,especially as micro/nanoelectronic and optoelectronic platforms.

关键词： Flexible large-area graphene nanofilm High carrier mobility Mid-infrared detection Electromagnetic interference shielding Heat transfer

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Distributed estimation on semi-supervised generalized linear model

The Journal of Machine Learning Research

引用

The Journal of Machine Learning Research 2024年第1期25卷 3735-3775页

作者： Jiyuan Tu Weidong Liu Xiaojun Mao School of Mathematics Shanghai University of Finance and Economics Shanghai China School of Mathematical Sciences MoE Key Lab of Artificial Intelligence Shanghai Jiao Tong University Shanghai China School of Mathematical Sciences Ministry of Education Key Laboratory of Scientific and Engineering Computing Shanghai Jiao Tong University Shanghai China

Semi-supervised learning is devoted to using unlabeled data to improve the performance of machine learning algorithms. In this paper, we study the semi-supervised generalized linear model (GLM) in the distributed setup. In the cases of single or multiple machines containing unlabeled data, we propose two distributed semi-supervised algorithms based on the distributed approximate Newton method. When the labeled local sample size is small, our algorithms still give a consistent estimation, while fully supervised methods fail to converge. Moreover, we theoretically prove that the convergence rate is greatly improved when sufficient unlabeled data exists. Therefore, the proposed method requires much fewer rounds of communications to achieve the optimal rate than its fully-supervised counterpart. In the case of the linear model, we prove the rate lower bound after one round of communication, which shows that rate improvement is essential. Finally, several simulation analyses and real data studies are provided to demonstrate the effectiveness of our method.

关键词： distributed learning semi-supervised learning generalized linear model

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