检索结果-内蒙古大学图书馆

arXiv 2023年

作者： Qian, Biao Wang, Yang Hong, Richang Wang, Meng Key Laboratory of Knowledge Engineering with Big Data Ministry of Education School of Computer Science and Information Engineering Hefei University of Technology China

data-free quantization (DFQ) recovers the performance of quantized network (Q) without accessing the original data, but generates the fake sample via a generator (G) by learning from full-precision network (P), which, however, is totally independent of Q, overlooking the adaptability of the knowledge from generated samples, i.e., informative or not to the learning process of Q, resulting into the overflow of generalization error. Building on this, several critical questions - how to measure the sample adaptability to Q under varied bit-width scenarios? how to generate the samples with large adaptability to improve Q's generalization? whether the largest adaptability is the best? To answer the above questions, in this paper, we propose an Adaptive data-Free Quantization (AdaDFQ) method, which revisits DFQ from a zero-sum game perspective upon the sample adaptability between two players - a generator and a quantized network. Following this viewpoint, we further define the disagreement and agreement samples to form two boundaries, where the margin is optimized to address the over-and-under fitting issues, so as to generate the samples with adaptive adaptability to Q. Our AdaDFQ reveals: 1) the largest adaptability is NOT the best for sample generation to benefit Q's generalization;2) the knowledge of the generated sample should not be informative to Q only, but also related to the category and distribution information of the training data for P. The theoretical and empirical analysis validate the advantages of AdaDFQ over the state-of-the-arts. Our code is available at https://***/hfutqian/AdaDFQ. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Clause-level Relationship-aware Math Word Problems Solver

引用

Machine Intelligence Research 2022年第5期19卷 425-438页

作者： Chang-Yang Wu Xin Lin Zhen-Ya Huang Yu Yin Jia-Yu Liu Qi Liu Gang Zhou Anhui Province Key Laboratory of Big Data Analysis and Application School of Data ScienceUniversity of Science and Technology of ChinaHefei 230026China Institute of Artificial Intelligence Hefei Comprehensive National Science CenterHefei 230088China Laboratory of Mathematical Engineering and Advanced Computing Information Engineering UniversityZhengzhou 450001China

Automatically solving math word problems,which involves comprehension,cognition,and reasoning,is a crucial issue in artificial intelligence *** math word problem solvers mainly work on word-level relationship extraction and the generation of expression solutions while lacking consideration of the clause-level *** this end,inspired by the theory of two levels of process in comprehension,we propose a novel clause-level relationship-aware math solver(CLRSolver)to mimic the process of human comprehension from lower level to higher ***,in the lower-level processes,we split problems into clauses according to their natural division and learn their *** the higher-level processes,following human′s multi-view understanding of clause-level relationships,we first apply a CNN-based module to learn the dependency relationships between clauses from word relevance in a local ***,we propose two novel relationship-aware mechanisms to learn dependency relationships from the clause semantics in a global ***,we enhance the representation of clauses based on the learned clause-level dependency *** expression generation,we develop a tree-based decoder to generate the mathematical *** conduct extensive experiments on two datasets,where the results demonstrate the superiority of our framework.

关键词： Artificial intelligence(AI) artificial neural network(ANN) computational mathematics machine intelligence machine learning

来源：评论

学校读者我要写书评

暂无评论

Calibration Signal Assisted Emitter Localization under Sensor Position Uncertainty

引用

IEEE Transactions on Aerospace and Electronic Systems 2025年第3期61卷 6913-6927页

作者： You, Ming-Yi Pu, Wenqiang Zhou, Rui Ye, Yun-Xia Xiao, Minrui Wang, Wei Shi, Qingjiang No.36 Research Institute of CETC National Key Laboratory of Electromagnetic Space Security Jiaxing314033 China The Chinese University of Hong Kong-Shenzhen Shenzhen Research Institute of Big Data Shenzhen518172 China Shanghai Jiaotong University School of Sensing Science and Engineering Shanghai200240 China Tongji University School of Software Engineering Shanghai200070 China

The uncertainty of sensor position significantly compromises the accuracy of source localization within the direct position determination (DPD) framework. This paper explores the use of an external calibrator that emits a calibration signal with a known position to mitigate the impact of sensor position uncertainty on localization accuracy. By utilizing the calibration signal, we develop a refined Gibbs sampling algorithm as the initial step to effectively address the high-dimensional optimization problem associated with sensor position calibration. In the second step, we account for measurement noise and estimation uncertainties in the calibrated sensor positions and propose a revised DPD method, which demonstrates greater resilience to sensor position uncertainty compared to existing methods. We also derive the Cramer-Rao Lower Bound for emitter position under scenarios both with and without an external calibrator. Numerical simulations are performed to evaluate the performance of our proposed algorithms against several benchmark methods, demonstrating the effectiveness of our approach. © 1965-2011 IEEE.

关键词： Cramer-Rao bounds

来源：评论

学校读者我要写书评

暂无评论

Rethinking data-Free Quantization as a Zero-Sum Game

arXiv

引用

arXiv 2023年

data-free quantization (DFQ) recovers the performance of quantized network (Q) without accessing the real data, but generates the fake sample via a generator (G) by learning from full-precision network (P) instead. However, such sample generation process is totally independent of Q, specialized as failing to consider the adaptability of the generated samples, i.e., beneficial or adversarial, over the learning process of Q, resulting into non-ignorable performance loss. Building on this, several crucial questions — how to measure and exploit the sample adaptability to Q under varied bit-width scenarios? how to generate the samples with desirable adaptability to benefit the quantized network? — impel us to revisit DFQ. In this paper, we answer the above questions from a game-theory perspective to specialize DFQ as a zero-sum game between two players — a generator and a quantized network, and further propose an Adaptability-aware Sample Generation (AdaSG) method. Technically, AdaSG reformulates DFQ as a dynamic maximization-vs-minimization game process anchored on the sample adaptability. The maximization process aims to generate the sample with desirable adaptability, such sample adaptability is further reduced by the minimization process after calibrating Q for performance recovery. The Balance Gap is defined to guide the stationarity of the game process to maximally benefit Q. The theoretical analysis and empirical studies verify the superiority of AdaSG over the state-of-the-arts. Our code is available at https://***/hfutqian/AdaSG. Copyright © 2023, The Authors. All rights reserved.

关键词： Game theory

来源：评论

学校读者我要写书评

暂无评论

Winter wheat phenology classification using stacking ensemble learning algorithm based on Sentinel-1A SAR images 5

Winter wheat phenology classification using stacking ensembl...

引用

5th International Conference on Geoscience and Remote Sensing Mapping, ICGRSM 2023

作者： Duan, Haoxin Yang, Huijin Zhao, Jianhui Li, Ning School of Computer and Information Engineering Henan University Kaifeng China Henan Province Engineering Research Center of Spatial Information Processing Kaifeng China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng China

ISBN: (纸本)9781510672789

Crop monitoring and phenology estimation based on the satellite systems have become an important research area due to high demand on crops. Synthetic Aperture Radar (SAR) is a kind of microwave remote sensing equipment, which has the advantage of all-weather and all-day, and can realize large-scale and periodic crop phenological monitoring. Besides, thanks to the high temporal resolution of new generation space-based sensors, it has been possible to monitor growth cycle of crops by classification algorithms. A stacking ensemble learning algorithm using time series Sentinel-1A SAR images for winter wheat phenology classification was proposed in this paper based on multiple machine learning models, including Random Forest (RF), Support Vector Machine (SVM), K-nearest Neighbor(K-NN), Naive Bayes (NB) and BP Neural Network (BP) models. The experimental results showed that, comparing with each single model, the stacking ensemble learning algorithm proposed in this paper had the optimal performance, with the highest overall recognition accuracy of 81.40%, demonstrating its effectiveness and application potential for winter wheat phenology identification. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Synthetic aperture radar

来源：评论

学校读者我要写书评

暂无评论

Strangeness S=-2 baryon-baryon interactions and femtoscopic correlation functions in covariant chiral effective field theory

引用

Chinese Physics C 2023年第2期47卷 174-189页

作者：刘志伟李凯文耿立升 School of Physics Beihang UniversityBeijing 102206China Medical Management Department CAS Ion Medical Technology Co.Ltd.Beijing 100190China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of Medicine and EngineeringBeihang UniversityKey Laboratory of Big Data-Based Precision Medicine(Beihang University)Ministry of Industry and Information TechnologyBeijing 100191China Beijing Key Laboratory of Advanced Nuclear Materials and Physics Beihang UniversityBeijing 102206China School of Physics and Microelectronics Zhengzhou UniversityZhengzhou 450001China

We study the baryon-baryon interactions with strangeness S=-2 and corresponding momentum correlation functions in leading order covariant chiral effective field *** relevant low energy constants are determined by fitting to the latest HAL QCD simulations,taking into account all the coupled *** the so-obtained strong interactions to the physical point and considering both quantum statistical effects and the Coulomb interaction,we calculate the ΛΛ and Ξ^(-)p correlation functions with a spherical Gaussian source and compare them with recent experimental *** find a good agreement between our predictions and the experimental measurements by using the source radius determined in proton-proton correlations,which demonstrates the consistency between theory,experiment,and lattice QCD ***,we predict the Σ^(+)Σ^(+),Σ^(+)Λ,and Σ^(+)Σ^(-) interactions and corresponding momentum correlation *** further investigate the influence of the source shape and size of the hadron pair on the correlation functions studied and show that the current data are not very sensitive to the source *** experimental measurements of the predicted momentum correlation functions will provide a non-trivial test of not only SU(3) flavor symmetry and its breaking but also the baryon-baryon interactions derived in covariant chiral effective field theory.

关键词： covariant chiral effective field theory momentum correlation functions baryon-baryon interactions

来源：评论

学校读者我要写书评

暂无评论

An Effective Security Comparison Protocol in Cloud Computing

引用

Computers, Materials & Continua 2023年第6期75卷 5141-5158页

作者： Yuling Chen Junhong Tao Tao Li Jiangyuan Cai Xiaojun Ren State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang550000China Guangxi Key Laboratory of Cryptography and Information Security Guilin University of Electronic TechnologyGuilin550000China POWERCHINA Guizhou Electric Power Engineering Co. Ltd.Guiyang550000China Blockchain Laboratory of Agricultural Vegetables Weifang University of Science and TechnologyWeifang261000China

With the development of cloud computing technology,more and more data owners upload their local data to the public cloud server for storage and *** this can save customers’operating costs,it also poses privacy and security *** challenges can be solved using secure multi-party computation(SMPC),but this still exposes more security *** cloud computing using SMPC,clients need to process their data and submit the processed data to the cloud server,which then performs the calculation and returns the results to each *** client and server must be *** there is cooperation or dishonest behavior between clients,some clients may profit from it or even disclose the private data of other *** paper proposes the SMPC based on a Partially-Homomorphic Encryption(PHE)scheme in which an addition homomorphic encryption algorithm with a lower computational cost is used to ensure data comparability and Zero-knowledge Proof(ZKP)is used to limit the client’s malicious *** addition,the introduction of Oblivious Transfer(OT)technology also ensures that the semi-honest cloud server knows nothing about private data,so that the cloud server of this scheme can calculate the correct data in the case of malicious participant models and safely return the calculation results to each ***,the security analysis shows that the scheme not only ensures the privacy of participants,but also ensures the fairness of the comparison protocol data.

关键词： Secure comparison protocols zero-knowledge proof homomorphic encryption cloud computing

来源：评论

学校读者我要写书评

暂无评论

Advances in anode interfacial materials for organic solar cells

Aggregate

引用

Aggregate 2024年第4期5卷 74-95页

作者： Menglan Lv Junhua Huang Xuanyan Luo Shan Yu Xu Wang Zhuo Wang Fei Pan Bin Zhang Liming Ding Engineering Research Center for Energy Conversion and Storage Technology of Guizhou School of Chemistry and Chemical EngineeringGuizhou UniversityGuiyangChina College of Big Data and Information Engineering Guizhou UniversityGuiyangChina School of Chemical Engineering Guizhou Institute of TechnologyGuiyangChina Center for Excellence in Nanoscience(CAS) Key Laboratory of Nanosystem and Hierarchical Fabrication(CAS)National Center for Nanoscience and TechnologyBeijingChina

Organic solar cells(OSCs)have attracted much interest in the past few decades because of their advantages,such as being lightweight,low cost,simple preparation process,and environmental *** researchers have made significant progress on the active layer materials of OSCs,the interface engineering is another entry point for upgrading the photovoltaic performance of ***,the interface modification materials,including anode interfacial materials and cathode interfacial materials,are two essential parts of interfacial layers for OSCs,in which the excellent interfacial materials can realize the very high-performance photovoltaic *** these interfacial materials,the anode interfacial layers(AILs)play a crucial role in improving photovoltaic *** review expresses a detailed conclusion of the development of anode interfacial materials and an outlook on future trends for OSCs.

关键词： anode interfacial materials organic solar cells power conversion efficiency

来源：评论

学校读者我要写书评

暂无评论

Application of remote sensing based on algorithm process technology inspection processing method

Application of remote sensing based on algorithm process tec...

引用

2022 International Conference on Signal Processing, Computer Networks, and Communications, SPCNC 2022

作者： Ge, Qiang Jiang, Kejian Han, Hongyu Liu, Huaizhou Zhang, Jing Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng475001 China School of Computer and Information Engineering Henan University Kaifeng475001 China

ISBN: (纸本)9781510664616

Aiming at a series of problems such as low evaluation efficiency of traditional algorithms, cumbersome process operation, high use cost and no complete algorithm inspection process system, this paper proposes an algorithm flow technology inspection processing system and method based on remote sensing applications, mainly including satellite product processing, algorithm processing, sample feature selection, sample extraction, and algorithm processing results comparison, It mainly realizes the functions of input, output and parameter adjustment required by different function functions, and designs an interface interaction system that adapts to the input and output elements required by different function modules. It realizes the modular, plug-in and componentized design of interface interaction of function modules, and obtains the evaluation system of algorithm credibility. © 2023 SPIE.

关键词： Inspection

来源：评论

学校读者我要写书评

暂无评论

Adaptive data-Free Quantization

Adaptive Data-Free Quantization

引用

Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Biao Qian Yang Wang Richang Hong Meng Wang Key Laboratory of Knowledge Engineering with Big Data Ministry of Education School of Computer Science and Information Engineering Hefei University of Technology China

data-free quantization (DFQ) recovers the performance of quantized network (Q) without the original data, but generates the fake sample via a generator (G) by learning from full-precision network (P), which, however, is totally independent of Q, overlooking the adaptability of the knowledge from generated samples, i.e., informative or not to the learning process of Q, resulting into the overflow of generalization error. Building on this, several critical questions — how to measure the sample adaptability to Q under varied bit-width scenarios? whether the largest adaptability is the best? how to generate the samples with adaptive adaptability to improve Q's generalization? To answer the above questions, in this paper, we propose an Adaptive data-Free Quantization (AdaDFQ) method, which revisits DFQ from a zero-sum game perspective upon the sample adaptability between two players — a generator and a quantized network. Following this viewpoint, we further define the disagreement and agreement samples to form two boundaries, where the margin between two boundaries is optimized to adaptively regulate the adaptability of generated samples to Q, so as to address the over-and-under fitting issues. Our AdaDFQ reveals: 1) the largest adaptability is NOT the best for sample generation to benefit Q's generalization; 2) the knowledge of the generated sample should not be informative to Q only, but also related to the category and distribution information of the training data for P. The theoretical and empirical analysis validate the advantages of AdaDFQ over the state-of-the-arts. Our code is available at https://***/hfutqian/AdaDFQ.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：