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IEEE Transactions on Artificial Intelligence 2024年第7期5卷 3595-3606页

作者： Liu, Haotian Zhou, Yadong Zhou, Yuxun Hu, Bowen Xi'an Jiaotong University Ministry of Education Key Laboratory for Intelligent Networks and Network Security Faculty of Electronic and Information Engineering Xi'an710049 China

Modern quantitative finance and portfolio-based investment hinge on the dependence structure among financial instruments (like stocks) for return prediction, risk management, and hedging. Several attempts have been made to leverage recent advancements in graph neural networks (GNNs) to achieve effective modeling to capture stock interactions. However, existing work suffers from the homogeneity and stationary of the predefined graph structure, and their reliance on hard-coded correlation-based relationships neglects the mutual intervention of different instruments. In this study, we propose the heterogeneous dual-dynamic attention network (HD2AT) to address these challenges in modeling the mutual interplay among stocks, across four key dimensions: heterogeneity, causality, structural dynamics, and lead-lag dynamics. More specifically, our method uncovers the causal interdependencies among instruments, dynamically inferring the heterogeneous network structure from real-time trading activities. Subsequently, we identify the cross-temporal propagation of interventions by integrating interactions at the node, time, and graph levels. Extensive experiments on real-world trading data demonstrate the superiority of the proposed framework over various baselines in terms of both return prediction and back-testing profitability. © 2020 IEEE.

关键词： Commerce

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Sparse recovery: from vectors to tensors

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National Science Review 2018年第5期5卷 756-767页

作者： Yao Wang Deyu Meng Ming Yuan School of Mathematics and Statistics Xi'an Jiaotong University Shenyang Institute of Automation Chinese Academy of Sciences Ministry of Education Key Lab of Intelligent Networks and Network Security Xi'an Jiaotong University Department of Statistics Columbia University

Recent advances in various fields such as telecommunications, biomedicine and economics, among others, have created enormous amount of data that are often characterized by their huge size and high dimensionality. It has become evident, from research in the past couple of decades, that sparsity is a flexible and powerful notion when dealing with these data, both from empirical and theoretical viewpoints. In this survey, we review some of the most popular techniques to exploit sparsity, for analyzing high-dimensional vectors, matrices and higher-order tensors.

关键词： high-dimensional data sparsity compressive sensing low-rank matrix recovery tensors

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Efficient quantum secret sharing scheme with two-particle entangled states

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Chinese Physics B 2011年第4期20卷 59-64页

作者：朱珍超张玉清付安民 Key Lab of Computer Networks and Information Security of Ministry of Education Xidian University National Computer Network Intrusion Protection Center Graduate University of the Chinese Academy of Sciences

This paper proposes a protocol for multi-party quantum secret sharing utilizing four non-orthogonal two-particle entangled states following some ideas in the schemes proposed by Liu et al. （2006 Chin. Phys. Lett. 23 3148） and Zhang et al. （2009 Chin. Phys. B 18 2149） respectively. The theoretical efficiency for qubits of the new protocol is improved from 50% to approaching 100%. All the entangled states can be used for generating the private key except those used for the eavesdropping check. The validity of a probable attack called opaque cheat attack to this kind of protocols is considered in the paper for the first time.

关键词： quantum secret sharing quantum entanglement Bell state nonorthogonal base

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Semantic correlation mining between images and texts with global semantics and local mapping 21

Semantic correlation mining between images and texts with gl...

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21st International Conference on MultiMedia Modeling, MMM 2015

作者： Xue, Jiao Du, Youtian Shui, Hanbing Ministry of Education Key Lab for Intelligent Networks and Network Security Xi’an Jiaotong University 710049 China

ISBN: (纸本)9783319144412

This paper proposes a novel approach for the modeling of semantic correlation between web images and texts. Our approach contains two processes of semantic correlation computing. One is to find the local media objects (LMOs), the components composing text (or image) documents, that match the global semantics of a given image(or text) document based on probabilistic latent semantic analysis (PLSA);The other is to make a direct mapping among LMOs with graph-based learning, with those LMOs achieved based on PLSA as a part of inputs. The two cooperating processes consider both dominant semantics and local subordinate parts of heterogeneous data. Finally, we compute the similarity between the obtained LMOs and a whole document of the same modality and then get the semantic correlation between textual and visual *** results demonstrate the effectiveness of the proposed approach. © Springer International Publishing Switzerland 2015.

关键词： Semantics

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Dynamic cohesion measurement for distributed system 1

Dynamic cohesion measurement for distributed system

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1st International Workshop on Specification, Comprehension, Testing, and Debugging of Concurrent Programs, SCTDCP 2016, co-located with ASE 2016

作者： Jin, Wuxia Liu, Ting Qu, Yu Chi, Jianlei Cui, Di Zheng, Qinghua Ministry of Education Key Lab for Intelligent Networks and Network Security Xi'An Jiaotong University Xi'an China

ISBN: (纸本)9781450345101

Instead of developing single-server software system for the powerful computers, the software is turning from large single-server to multi-server system such as distributed system. This change introduces a new challenge for the software quality measurement, since the current software analysis methods for single-server software could not observe and assess the correlation among the components on different nodes. In this paper, a new dynamic cohesion approach is proposed for distributed system. We extend Calling network model for distributed system by differentiating methods of components deployed on different nodes. Two new cohesion metrics are proposed to describe the correlation at component level, by extending the cohesion metric of single-server software system. The experiments, conducted on a distributed systems-Netflix RSS Reader, present how to trace the various system functions accomplished on three nodes, how to abstract dynamic behaviors using our model among different nodes and how to evaluate the software cohesion on distributed system. © 2016 ACM.

关键词： Adhesion

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A Feasible Graph Partition Framework for Random Walks Implemented by Parallel Computing in Big Graph 34

A Feasible Graph Partition Framework for Random Walks Implem...

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第三十四届中国控制会议

作者： LIU Xiaoming ZHOU Yadong GUAN Xiaohong SUN Xiaoxiao Ministry of Education Key Lab for Intelligent Networks and Network Security Xi'an Jiaotong University Center for Intelligent and Networked Systems and TNLIST Lab Tsinghua University

ISBN: (纸本)9781467374439

Graph partition is a fundamental problem of parallel computing for big graph data. Many graph partition algorithms have been proposed to solve the problem in various applications, such as matrix computations and Page Rank, etc., but none has pay attention to random walks. Random walks is a widely used method to explore graph structure in lots of fields. The challenges of graph partition for random walks include the large number of times of communication between partitions, too many replications of the vertices, unbalanced partition, etc. In this paper, we propose a feasible graph partition framework for random walks implemented by parallel computing in big graph. The framework is based on two optimization functions to reduce the bandwidth, memory and storage cost in the condition that the load balance is guaranteed. In this framework, several greedy graph partition algorithms are proposed. We also use five metrics from different perspectives to evaluate the performance of these algorithms. By running the algorithms on the big graph data set of real world, the experimental results show that these algorithms in the framework are capable of solving the problem of graph partition for random walks for different needs, e.g. the best result is improved more than 70 times in reducing the times of communication.

关键词： Graph partition,parallel graph computing,big graph,random walks,optimization functions,metrics

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A dynamic secret-based encryption method in smart grids wireless communication

A dynamic secret-based encryption method in smart grids wire...

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2012 IEEE Innovative Smart Grid Technologies - Asia, ISGT Asia

作者： Sun, Yao Mao, Yashan Liu, Ting Sun, Yanan Liu, Yang Guan, Xiaohong Ministry of Education Key Lab. for Intelligent Networks and Network Security Xi'an Jiaotong University China

ISBN: (纸本)9781467312219

Numerous devices in smart grids are deployed at millions of buildings and streets, connected with wireless network and applied the uniform public protocols and standards. It indicates high-risk threats on the privacy and security of smart grids wireless communication. In this paper, two attack scenarios are presented to show the vulnerability of smart grids, and a new encryption method based on dynamic secret is proposed to protect wireless communication. © 2012 IEEE.

关键词： Cryptography

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Demand Response Allocation to Hedge LMP Variability through Optimal Basis Invariancy Set of Linear Economic Dispatching 35

Demand Response Allocation to Hedge LMP Variability through ...

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第35届中国控制会议

作者： YAO Nana WU Jiang GUAN Xiaohong CHENG Xingrui Ministry of Education Key Lab for Intelligent Networks and Network Security Xi'an Jiaotong University Department of Automation and TNLIST Lab Tsinghua University

ISBN: (纸本)9781509009107

With more wind power permeating into the power grid, one of the issues caused by its random output is the fluctuation of locational marginal price(LMP) which is also affected by the fluctuation of system load. However, the fluctuation of electricity price will affect many aspects of the national economy. In order to cope with this issue, a demand response(DR) allocation mechanism is presented in this paper to hedge the LMP variability which is equal to keep the optimal basis invariant. Whether DR is available to keep the optimal basis optimal when wind power and load fluctuate within certain ranges is estimated from the perspective of sensitivity analysis of linear programming. Finally, the scheme is applied to test case IEEE 31 bus system and its feasibility is proved by the simulation results.

关键词： LMP fluctuation optimal basis invariance demand response sensitivity analysis

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Hierarchical Task Planning for Power Line Flow Regulation

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 29-40页

作者： Chenxi Wang Youtian Du Yanhao Huang Yuanlin Chang Zihao Guo the Ministry of Education Key Lab for Intelligent Networks and Network Security Xi'an Jiaotong UniversityXi'an 713599China the State Key Laboratory of Power Grid Safety and Energy Conservation China Electric Power Research InstituteBeijing 100192China

The complexity and uncertainty in power systems cause great challenges to controlling power *** a popular data-driven technique,deep reinforcement learning(DRL)attracts attention in the control of power ***,DRL has some inherent drawbacks in terms of data efficiency and *** paper presents a novel hierarchical task planning(HTP)approach,bridging planning and DRL,to the task of power line flow ***,we introduce a threelevel task hierarchy to model the task and model the sequence of task units on each level as a task planning-Markov decision processes(TP-MDPs).Second,we model the task as a sequential decision-making problem and introduce a higher planner and a lower planner in HTP to handle different levels of task *** addition,we introduce a two-layer knowledge graph that can update dynamically during the planning procedure to assist *** results conducted on the IEEE 118-bus and IEEE 300-bus systems demonstrate our HTP approach outperforms proximal policy optimization,a state-of-the-art deep reinforcement learning(DRL)approach,improving efficiency by 26.16%and 6.86%on both systems.

关键词： Knowledge graph power line flow regulation reinforcement learning task planning

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Phase detection based range estimation with a dual-band robust Chinese remainder theorem

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Science China(Information Sciences) 2014年第2期57卷 18-26页

作者： YANG Bin WANG WenJie XIA XiangGen YIN QinYe Ministry of Education (MOE) Key Laboratory for Intelligent Networks and Network Security School of Electronics and Information EngineeringXi’an Jiaotong University Department of Electrical and Computer Engineering University of Delaware

Range estimation with multifrequency phases is a common practice in localization *** challenge of this method is the phase *** Chinese remainder theorem(CRT)based phase unwrapping algorithms have been proposed to solve the problem,where the wavelengths of the multifrequency signals need to be pair-wisely co-prime after they are divided by their greatest common divisor(gcd).This condition may limit the application in *** this paper,a novel way based on a dual-band robust CRT is presented to reconstruct the distance from dual-band wrapped phases,where the pair-wisely co-prime condition is not necessarily *** more wrapped phases are involved to reconstruct the distance,the method can significantly enlarge the reconstruction range compared to the single band solution.

关键词： range estimation Chinese remainder theorem(CRT) robustness dual band

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