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Hongwei Zhang

Hongwei Zhang appears in the imported research catalog. Authorship, coauthor and topic links are available while profile ownership is still unclaimed.

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math.OCcond-mat.mtrl-sciArtificial Intelligenceeess.SYMachine LearningSystems and ControlNetworking and Internet Architecturenlin.AOcond-mat.mes-hallcond-mat.str-elcond-mat.supr-conCryptography and SecurityInformation Retrieval

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Published work

17 published item(s)

preprint2026arXiv

UxSID: Semantic-Aware User Interests Modeling for Ultra-Long Sequence

Modeling ultra-long user sequences involves a difficult trade-off between efficiency and effectiveness. While current paradigms rely on either item-specific search or item-agnostic compression, we propose UxSID, a framework exploring a third path: semantic-group shared interest memory. By utilizing Semantic IDs (SIDs) and a dual-level attention strategy, UxSID captures target-aware preferences without the heavy cost of item-specific models. This end-to-end architecture balances computational parsimony with semantic awareness, achieving state-of-the-art performance and a 0.337% revenue lift in large-scale advertising A/B test.

0 citations0 reviewsNo code linkedOpen access
preprint2023arXiv

Leaderless Consensus of Heterogeneous Multiple Euler-Lagrange Systems with Unknown Disturbance

This paper studies the leaderless consensus problem of {heterogeneous} multiple networked Euler-Lagrange systems subject to persistent disturbances with unknown constant biases, amplitudes, initial phases, and frequencies. The main characteristic of this study is that none of the agents has information of a common reference model or of a common reference trajectory. Therefore, the agents must simultaneously and in a distributed way: achieve consensus to a common reference model (group model); achieve consensus to a common reference trajectory; {and} reject the unknown disturbances. We show that this is possible via a suitable combination of techniques of distributed `observers', internal model principle, and adaptive regulation. The proposed design generalizes recent results on group model learning, which have been studied for linear agents over undirected networks. In this work, group model learning is achieved for Euler-Lagrange dynamics over directed networks in the presence of persistent unknown disturbances.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Adaptive Cooperative Tracking and Parameter Estimation of an Uncertain Leader over General Directed Graphs

This paper studies cooperative tracking problem of heterogeneous Euler-Lagrange systems with an uncertain leader. Different from most existing works, system dynamic knowledge of the leader node is unaccessible to any follower node in our paper. Distributed adaptive observers are designed for all follower nodes, simultaneously estimate the state and parameters of the leader node. The observer design does not rely on the frequency knowledge of the leader node, and the estimation errors are shown to converge to zero exponentially. Moreover, the results are applied to general directed graphs, where the symmetry of Laplacian matrix does not hold. This is due to two newly developed Lyapunov equations, which solely depend on communication network topologies. Interestingly, using these Lyapunov equations, many results of multi-agent systems over undirected graphs can be extended to general directed graphs. Finally, this paper also advances the knowledge base of adaptive control systems by providing a main tool in the analysis of parameter convergence for adaptive observers.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Defending Adversarial Examples by Negative Correlation Ensemble

The security issues in DNNs, such as adversarial examples, have attracted much attention. Adversarial examples refer to the examples which are capable to induce the DNNs return completely predictions by introducing carefully designed perturbations. Obviously, adversarial examples bring great security risks to the development of deep learning. Recently, Some defense approaches against adversarial examples have been proposed, however, in our opinion, the performance of these approaches are still limited. In this paper, we propose a new ensemble defense approach named the Negative Correlation Ensemble (NCEn), which achieves compelling results by introducing gradient directions and gradient magnitudes of each member in the ensemble negatively correlated and at the same time, reducing the transferability of adversarial examples among them. Extensive experiments have been conducted, and the results demonstrate that NCEn can improve the adversarial robustness of ensembles effectively.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Learning nonlinear dynamics in synchronization of knowledge-based leader-following networks

Knowledge-based leader-following synchronization of heterogeneous nonlinear multi-agent systems is a challenging problem since the leader's dynamic information is unknown to any follower node. This paper proposes a learning-based fully distributed observer for a class of nonlinear leader systems, which can simultaneously learn the leader's dynamics and states. This class of leader dynamics is rather general and does not require a bounded Jacobian matrix. Based on this learning-based distributed observer, we further synthesize an adaptive distributed control law for solving the leader-following synchronization problem of multiple Euler-Lagrange systems subject to an uncertain nonlinear leader system. The results are illustrated by a simulation example.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Coupling effect and pole assignment in trajectory regulation of multi-agent systems

This paper revisits a well studied leader-following consensus problem of linear multi-agent systems, while aiming at follower nodes' transient performance. Conventionally, when not all follower nodes have access to the leader's state information, distributed observers are designed to estimate the leader's state, and the observers are coupled via communication network. Then each follower node only needs to track its observer's state independently, without interacting with its neighbors. This paper deliberately introduces certain coupling effect among follower nodes, such that the follower nodes tend to converge to each other cooperatively on the way they converge to the leader. Moreover, by suitably designing the control law, the poles of follower nodes can be assigned as desired, and thus transient tracking performance can also be adjusted.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Large anomalous Hall angle in a topological semimetal candidate TbPtBi

The magnetotransport properties in antiferromagnetic half-Heusler single crystals of TbPtBi, a magnetic-field-induced topological semimetal with simple band structure, are investigated. We found that a nonmonotonic magnetic field dependence of the anomalous Hall resistivity in a high magnetic field (B>7T), which come from the change of band structure induced by the Zeeman-like splitting when applying the external magnetic field. The experiment results show that credible anomalous Hall resistivity and conductivity reach up to 0.6798mΩcm and 125Ω-1cm-1, respectively. A large AHA up to 33% is obtained in TbPtBi, which is comparable to typical ferromagnetic Weyl semimetal. The analysis of results show it should be attributed to topological band around EF and low carrier density.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Stochastic Graph Recurrent Neural Network

Representation learning over graph structure data has been widely studied due to its wide application prospects. However, previous methods mainly focus on static graphs while many real-world graphs evolve over time. Modeling such evolution is important for predicting properties of unseen networks. To resolve this challenge, we propose SGRNN, a novel neural architecture that applies stochastic latent variables to simultaneously capture the evolution in node attributes and topology. Specifically, deterministic states are separated from stochastic states in the iterative process to suppress mutual interference. With semi-implicit variational inference integrated to SGRNN, a non-Gaussian variational distribution is proposed to help further improve the performance. In addition, to alleviate KL-vanishing problem in SGRNN, a simple and interpretable structure is proposed based on the lower bound of KL-divergence. Extensive experiments on real-world datasets demonstrate the effectiveness of the proposed model. Code is available at https://github.com/StochasticGRNN/SGRNN.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

Single Crystal Growth of the New Pressure-induced-superconductor CrAs via Chemical Vapor Transport

Mono-arsenide CrAs, endures a helical anti-ferromagnetic order transition at~ 265 K under ambient pressure. Recently, pressure-induced-superconductivity was discovered vicinity to the helical anti-ferromagnetic order in CrAs[Wei Wu et al., Nature Communications 5, 5508 (2014).]. However, the size of crystal grown via tin flux method is as small as 1 mm in longest dimension. In this work, we report the single crystal growth of CrAs with size of 1 * 5 * 1 mm3 via chemical vapor transport method and its physical properties.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

Transport evidence for the three-dimensional Dirac semimetal phase in ZrTe5

Topological Dirac semimetal is a newly discovered class of materials and has attracted intense attentions. This material can be viewed as a three-dimensional (3D) analogue of graphene and has linear energy dispersion in bulk, leading to a range of exotic transport properties. Here we report direct quantum transport evidence of 3D Dirac semimetal phase of layered material ZrTe5 by angular dependent magnetoresistance measurements under high magnetic fields up to 31 Tesla. We observed very clear negative longitudinal magnetoresistance induced by chiral anomaly under the condition of the magnetic field aligned only along the current direction. Pronounced Shubnikov-de Hass (SdH) quantum oscillations in both longitudinal magnetoresistance and transverse Hall resistance were observed, revealing anisotropic light cyclotron masses and high mobility of the system. In particular, a nontrivial π-Berry phase in the SdH gives clear evidence for 3D Dirac semimetal phase. Furthermore, we observed clear Landau Level splitting under high magnetic field, suggesting possible splitting of Dirac point into Weyl points due to broken time reversal symmetry. Our results indicate that ZrTe5 is an ideal platform to study 3D massless Dirac and Weyl fermions in a layered compound.

0 citations0 reviewsNo code linkedOpen access
preprint2015arXiv

A Multi-Scale Spatiotemporal Perspective of Connected and Automated Vehicles: Applications and Wireless Networking

Wireless communication is a basis of the vision of connected and automated vehicles (CAVs). Given the heterogeneity of both wireless communication technologies and CAV applications, one question that is critical to technology road-mapping and policy making is which communication technology is more suitable for a specific CAV application. Focusing on the technical aspect of this question, we present a multi-scale spatiotemporal perspective of wireless communication technologies as well as canonical CAV applications in active safety, fuel economy and emission control, vehicle automation, and vehicular infotainment. Our analysis shows that CAV applications in the regime of small spatiotemporal scale communication requirements are best supported by V2V communications, applications in the regime of large spatiotemporal scale communication requirements are better supported by cellular communications, and applications in the regime of small spatial scale but medium-to-large temporal scale can be supported by both V2V and cellular communications and provide the opportunity of leveraging heterogeneous communication resources.

0 citations0 reviewsNo code linkedOpen access
preprint2015arXiv

Large low-field positive magnetoresistance in nonmagnetic half-Heusler ScPtBi single crystal

High-quality nonmagnetic half-Heusler ScPtBi single crystals were synthesized by a Bi self-flux method. This compound was revealed to be a hole-dominated semimetal with a large low-field magnetoresistance up to 240% at 2K in a magnetic field of 1T. Magneto-transport measurements demonstrated that the large low-field magnetoresistance effect resulted from the coexistence of field-induced metal-semiconductor transition and weak-antilocalization effect. Moreover, Hall measurements indicated that ScPtBi single crystal showed a high mobility over a wide temperature region even up to room temperature (4050 cm2V-1s-1 at 2K - 2016 cm2V-1s-1 at 300K). These findings not only suggest the nonmagnetic ScPtBi semimetal a potential material candidate for applications in high-sensitivity magnetic sensors, but also are of great significance to comprehensively understand the rare-earth based half-Heusler compounds.

0 citations0 reviewsNo code linkedOpen access
preprint2014arXiv

A Maximal Concurrency and Low Latency Distributed Scheduling Protocol for Wireless Sensor Networks

Existing work that schedules concurrent transmissions collision-free suffers from low channel utilization. We propose the Optimal Node Activation Multiple Access (ONAMA) protocol to achieve maximal channel spatial reuse through a distributed maximal independent set (DMIS) algorithm. To overcome DMIS's excessive delay in finding a maximal independent set, we devise a novel technique called pipelined precomputation that decouples DMIS from data transmission. We implement ONAMA on resource-constrained TelosB motes using TinyOS. Extensive measurements on two testbeds independently attest to ONAMA's superb performance compared to existing work: improving concurrency, throughput, and delay by a factor of 3.7, 3.0, and 5.3, respectively, while still maintaining reliability.

0 citations0 reviewsNo code linkedOpen access
preprint2014arXiv

A Mean-Variance Control Framework for Platoon Control Problems: Weak Convergence Results and Applications on Reduction of Complexity

This paper introduces a new approach of treating platoon systems using mean-variance control formulation. The underlying system is a controlled switching diffusion in which the random switching process is a continuous-time Markov chain. This switching process is used to represent random environment and other random factors that cannot be given by stochastic differential equations driven by a Brownian motion. The state space of the Markov chain is large in our setup, which renders practically infeasible a straightforward implementation of the mean-variance control strategy obtained in the literature. By partitioning the states of the Markov chain into sub-groups (or clusters) and then aggregating the states of each cluster as a super state, we are able to obtain a limit system of much reduced complexity. The justification of the limit system is rigorously supported by establishing certain weak convergence results.

0 citations0 reviewsNo code linkedOpen access
preprint2014arXiv

Near-Optimal Mean-Variance Controls under Two-time-scale Formulations and Applications

Although the mean-variance control was initially formulated for financial portfolio management problems in which one wants to maximize expected return and control the risk, our motivations also stem from highway vehicle platoon controls that aim to maximize highway utility while ensuring zero accident. This paper develops near-optimal mean-variance controls of switching diffusion systems. To reduce the computational complexity, with motivations from earlier work on singularly perturbed Markovian systems \cite{SethiZ94,Yin&Zhang,GZB}, we use a two-time-scale formulation to treat the underlying systems, which is represented by use of a small parameter. As the small parameter goes to 0, we obtain a limit problem. Using the limit problem as a guide, we construct controls for the original problem, and show that the control so constructed is nearly optimal.

0 citations0 reviewsNo code linkedOpen access
preprint2012arXiv

Stable magnetostructural coupling with tunable magnetoresponsive effects in hexagonal phase-transition ferromagnets

The magnetostructural coupling between the structural and the magnetic transition plays a crucial role in magnetoresponsive effects in a martensitic-transition system. A combination of various magnetoresponsive effects based on this coupling may facilitate the multifunctional applications of a host material. Here, we demonstrate a possibility to obtain a stable magnetostructural coupling in a broad temperature window from 350 to 70 K, showing tunable magnetoresponsive effects, based on simultaneous manipulation of the phase stability and the magnetic structure by suitable chemical substitution of iron in MnNiGe. The resultant MnNiGe:Fe exhibits a magnetic-field-induced martensitic transition from paramagnetic austenite to ferromagnetic martensite, featuring (i) a large volume increase, (ii) a distinct magnetization change, (iii) small thermal hysteresis and (iv) a giant negative magnetocaloric effect. The results indicate that stable magnetostructural coupling is accessible in hexagonal phase-transition systems to attain the magnetoresponsive effects with broad tunability.

0 citations0 reviewsNo code linkedOpen access
preprint2011arXiv

Magnetostructural Transformation and Magnetoresponsive Properties of MnNiGe1-xSnx Alloys

The martensitic and magnetic phase transformations in MnNiGe1-xSnx (0 \leq x \leq 0.200) alloys were investigated using X-ray diffraction (XRD), differential thermal analysis (DTA) and magnetization measurements. Results indicate that the increasing Sn substitution in MnNiGe1-xSnx results in (i) decrease of martensitic transformation temperature from 460 to 100 K and (ii) conversion of AFM spiral to antiparallel AFM strcuture in martensite. Based on these, the remarkable magnetic-field-induced PM/spiral-AFM and FM/AFM magnetostructural transformations and, large positive and negative magnetocaloric effects are obtained. The magnetoresponsive effects of MnNiGe1-xSnx alloys are enhanced by Sn substitution. A structural and magnetic phase diagram of MnNiGe1-xSnx alloys has been proposed.

0 citations0 reviewsNo code linkedOpen access