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Critical Multipliers in Semidefinite Programming [article]

Tianyu Zhang, Liwei Zhang
2018 arXiv   pre-print
When the set K in (1.1) belongs to the class of C 2 -cone reducible sets, Ding, Sun and Zhang [7] showed that under the Robinson constaint qualification, the KKT solution mapping is robustly isolated  ... 
arXiv:1801.02218v1 fatcat:ls4oouiomzhybf227or5spmjsi

Background Segmentation for Vehicle Re-Identification [article]

Mingjie Wu, Yongfei Zhang, Tianyu Zhang, Wenqi Zhang
2019 arXiv   pre-print
Vehicle re-identification (Re-ID) is very important in intelligent transportation and video surveillance.Prior works focus on extracting discriminative features from visual appearance of vehicles or using visual-spatio-temporal information.However, background interference in vehicle re-identification have not been explored.In the actual large-scale spatio-temporal scenes, the same vehicle usually appears in different backgrounds while different vehicles might appear in the same background,
more » ... will seriously affect the re-identification performance. To the best of our knowledge, this paper is the first to consider the background interference problem in vehicle re-identification. We construct a vehicle segmentation dataset and develop a vehicle Re-ID framework with a background interference removal (BIR) mechanism to improve the vehicle Re-ID performance as well as robustness against complex background in large-scale spatio-temporal scenes. Extensive experiments demonstrate the effectiveness of our proposed framework, with an average 9% gain on mAP over state-of-the-art vehicle Re-ID algorithms.
arXiv:1910.06613v1 fatcat:xixds46b4bgmxgls2nyhaotmbq

Single Camera Training for Person Re-identification [article]

Tianyu Zhang, Lingxi Xie, Longhui Wei, Yongfei Zhang, Bo Li, Qi Tian
2019 arXiv   pre-print
In addition, some researchers designed complex network architectures to extract more robust and discriminative features (Wei et al. 2017; Zhang et al. 2017; Liu et al. 2018) .  ...  In addition, some researchers designed complex network architectures to extract more robust and discriminative features (Wei et al. 2017; Zhang et al. 2017; Liu et al. 2018 (Chen et al. 2017 ) proposed  ... 
arXiv:1909.10848v1 fatcat:wxdpf2bazvbztnofubb6ujs22m

Engineering Dissipative Quasicrystals [article]

Tianyu Li, Yong-Sheng Zhang, Wei Yi
2021 arXiv   pre-print
We discuss the systematic engineering of quasicrystals in open quantum systems where quasiperiodicity is introduced through purely dissipative processes. While the resulting short-time dynamics is governed by non-Hermitian variants of the Aubry-Andre-Harper model, we demonstrate how phases and phase transitions pertaining to the non-Hermitian quasicrystals fundamentally change the long-time, steady-state-approaching dynamics under the Lindblad master equation. Our schemes are based on an exact
more » ... apping between the eigenspectrum of the Liouvillian superoperator with that of the non-Hermitian Hamiltonian, under the condition of quadratic fermionic systems subject to linear dissipation. Our work suggests a systematic route toward engineering exotic quantum dynamics in open systems, based on insights of non-Hermitian physics.
arXiv:2111.14436v2 fatcat:mcot7vsxuzcola4wbcszvxjve4

Modeling Biofilms: From Genes to Communities

Tianyu Zhang
2017 Processes  
Wang and Zhang [15] give a chronological review of some biofilm models developed from the 1980s to the early 2000s.  ...  Zhang et al. [50] developed a theory for the analysis and prediction of the spatial and temporal patterns of gene and protein expression within microbial biofilms based on similar ideas.  ... 
doi:10.3390/pr5010005 fatcat:njuqrexcd5amjlcapdjh33ceju

Learning to Learn Graph Topologies [article]

Xingyue Pu, Tianyue Cao, Xiaoyun Zhang, Xiaowen Dong, Siheng Chen
2021 arXiv   pre-print
Learning a graph topology to reveal the underlying relationship between data entities plays an important role in various machine learning and data analysis tasks. Under the assumption that structured data vary smoothly over a graph, the problem can be formulated as a regularised convex optimisation over a positive semidefinite cone and solved by iterative algorithms. Classic methods require an explicit convex function to reflect generic topological priors, e.g. the ℓ_1 penalty for enforcing
more » ... sity, which limits the flexibility and expressiveness in learning rich topological structures. We propose to learn a mapping from node data to the graph structure based on the idea of learning to optimise (L2O). Specifically, our model first unrolls an iterative primal-dual splitting algorithm into a neural network. The key structural proximal projection is replaced with a variational autoencoder that refines the estimated graph with enhanced topological properties. The model is trained in an end-to-end fashion with pairs of node data and graph samples. Experiments on both synthetic and real-world data demonstrate that our model is more efficient than classic iterative algorithms in learning a graph with specific topological properties.
arXiv:2110.09807v1 fatcat:aj5tgcums5bnhhtfrwwexinuce

CaT: Weakly Supervised Object Detection with Category Transfer [article]

Tianyue Cao, Lianyu Du, Xiaoyun Zhang, Siheng Chen, Ya Zhang, Yan-Feng Wang
2021 arXiv   pre-print
. * Xiaoyun Zhang is the corresponding author.  ... 
arXiv:2108.07487v1 fatcat:fmjdq3lto5dynd2xaja2fnyocq

Spatiotemporal Transformer for Video-based Person Re-identification [article]

Tianyu Zhang, Longhui Wei, Lingxi Xie, Zijie Zhuang, Yongfei Zhang, Bo Li, Qi Tian
2021 arXiv   pre-print
Recently, the Transformer module has been transplanted from natural language processing to computer vision. This paper applies the Transformer to video-based person re-identification, where the key issue is to extract the discriminative information from a tracklet. We show that, despite the strong learning ability, the vanilla Transformer suffers from an increased risk of over-fitting, arguably due to a large number of attention parameters and insufficient training data. To solve this problem,
more » ... e propose a novel pipeline where the model is pre-trained on a set of synthesized video data and then transferred to the downstream domains with the perception-constrained Spatiotemporal Transformer (STT) module and Global Transformer (GT) module. The derived algorithm achieves significant accuracy gain on three popular video-based person re-identification benchmarks, MARS, DukeMTMC-VideoReID, and LS-VID, especially when the training and testing data are from different domains. More importantly, our research sheds light on the application of the Transformer on highly-structured visual data.
arXiv:2103.16469v1 fatcat:xtkwdlg62vbilbndbvmgqww56y

One-Pass Error Bounded Trajectory Simplification [article]

Xuelian Lin, Shuai Ma, Han Zhang, Tianyu Wo, Jinpeng Huai
2017 arXiv   pre-print
Nowadays, various sensors are collecting, storing and transmitting tremendous trajectory data, and it is known that raw trajectory data seriously wastes the storage, network band and computing resource. Line simplification (LS) algorithms are an effective approach to attacking this issue by compressing data points in a trajectory to a set of continuous line segments, and are commonly used in practice. However, existing LS algorithms are not sufficient for the needs of sensors in mobile devices.
more » ... In this study, we first develop a one-pass error bounded trajectory simplification algorithm (OPERB), which scans each data point in a trajectory once and only once. We then propose an aggressive one-pass error bounded trajectory simplification algorithm (OPERB-A), which allows interpolating new data points into a trajectory under certain conditions. Finally, we experimentally verify that our approaches (OPERB and OPERB-A) are both efficient and effective, using four real-life trajectory datasets.
arXiv:1702.05597v1 fatcat:k4vyonw54nglvawgmm5ij4mgxm

Apply Artificial Neural Network to Solving Manpower Scheduling Problem [article]

Tianyu Liu, Lingyu Zhang
2021 arXiv   pre-print
The manpower scheduling problem is a kind of critical combinational optimization problem. Researching solutions to scheduling problems can improve the efficiency of companies, hospitals, and other work units. This paper proposes a new model combined with deep learning to solve the multi-shift manpower scheduling problem based on the existing research. This model first solves the objective function's optimized value according to the current constraints to find the plan of employee arrangement
more » ... tially. It will then use the scheduling table generation algorithm to obtain the scheduling result in a short time. Moreover, the most prominent feature we propose is that we will use the neural network training method based on the time series to solve long-term and long-period scheduling tasks and obtain manpower arrangement. The selection criteria of the neural network and the training process are also described in this paper. We demonstrate that our model can make a precise forecast based on the improvement of neural networks. This paper also discusses the challenges in the neural network training process and obtains enlightening results after getting the arrangement plan. Our research shows that neural networks and deep learning strategies have the potential to solve similar problems effectively.
arXiv:2105.03541v1 fatcat:ij56pjk4crbkdnkcinzspjdon4

Interactive Rainbow Score: A Visual-centered Multimodal Flute Tutoring System [article]

Daniel Chin, Yian Zhang, Tianyu Zhang, Jake Zhao, Gus G. Xia
2020 arXiv   pre-print
Learning to play an instrument is intrinsically multimodal, and we have seen a trend of applying visual and haptic feedback in music games and computer-aided music tutoring systems. However, most current systems are still designed to master individual pieces of music; it is unclear how well the learned skills can be generalized to new pieces. We aim to explore this question. In this study, we contribute Interactive Rainbow Score, an interactive visual system to boost the learning of
more » ... g, the general musical skill to read music and map the visual representations to performance motions. The key design of Interactive Rainbow Score is to associate pitches (and the corresponding motions) with colored notation and further strengthen such association via real-time interactions. Quantitative results show that the interactive feature on average increases the learning efficiency by 31.1%. Further analysis indicates that it is critical to apply the interaction in the early period of learning.
arXiv:2004.13908v1 fatcat:ujbdoaybu5ckbogmkmx5gl5gge

Prototyping and Production of Polymeric Microfluidic Chip [chapter]

Honggang Zhang, Haoyang Zhang, Tianyu Guan, Xiangyu Wang, Nan Zhang
2021 Advances in Micro- and Nanofluidics [Working Title]  
Notes/thanks/other declarations Thanks Honggang Zhang, Haoyang Zhang, Tianyu Guan, and Xiangyu Wang for their original draft writing and Dr. Nan Zhang for his review & editing, and supervision.  ... 
doi:10.5772/intechopen.96355 fatcat:gk4ghm36lneajfp7cx6w43came

Subwavelength Silicon Nanoblocks for Directional Emission Manipulation

Tianyue Zhang, Xuewei Li, Jian Xu, Xiaoming Zhang, Zi-Lan Deng, Xiangping Li
2020 Nanomaterials  
Manipulating the light emission direction and boosting its directivity have essential importance in integrated nanophotonic devices. Here, we theoretically propose a single dielectric silicon nanoblock as an efficient, multifunctional and ultracompact all-dielectric nanoantenna to direct light into a preferential direction. Unidirectional scattering of a plane wave as well as switchable directive emission fed by a localized emitter are demonstrated within the nanoantenna. The high
more » ... es are revealed to originate from a variety of mechanisms that can coexist within a single nanoblock, which contribute to the far-field radiation patterns of the outcoming light, thanks to the wealth of multipolar electric and magnetic resonances. The efficient beam redirections are also observed, which are sensitive to the local configurations of the emitter antenna coupled system. The designed antenna, with extreme geometry simplicity, ultracompact and low-loss features, could be favorable for highly sensitive sensing as well as applications in optical nanocircuits.
doi:10.3390/nano10061242 pmid:32604754 pmcid:PMC7353081 fatcat:ztdk455aavhurf66dxvotrejlq

An Intelligent Model for Solving Manpower Scheduling Problems [article]

Lingyu Zhang and Tianyu Liu and Yunhai Wang
2021 arXiv   pre-print
The manpower scheduling problem is a critical research field in the resource management area. Based on the existing studies on scheduling problem solutions, this paper transforms the manpower scheduling problem into a combinational optimization problem under multi-constraint conditions from a new perspective. It also uses logical paradigms to build a mathematical model for problem solution and an improved multi-dimensional evolution algorithm for solving the model. Moreover, the constraints
more » ... ussed in this paper basically cover all the requirements of human resource coordination in modern society and are supported by our experiment results. In the discussion part, we compare our model with other heuristic algorithms or linear programming methods and prove that the model proposed in this paper makes a 25.7% increase in efficiency and a 17% increase in accuracy at most. In addition, to the numerical solution of the manpower scheduling problem, this paper also studies the algorithm for scheduling task list generation and the method of displaying scheduling results. As a result, we not only provide various modifications for the basic algorithm to solve different condition problems but also propose a new algorithm that increases at least 28.91% in time efficiency by comparing with different baseline models.
arXiv:2105.03540v1 fatcat:umtmjtkt7zgtlhtaqnjz6itazu

Identifying Grey-box Thermal Models with Bayesian Neural Networks [article]

Md Monir Hossain, Tianyu Zhang, Omid Ardakanian
2020 arXiv   pre-print
For example, Zhang et al. [39] employ transfer learning to transfer an occupancy estimation model across different buildings.  ... 
arXiv:2009.05889v1 fatcat:urh6qrhcvjf3pi52n2drsfvzue
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