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学者姓名：赵欣苑
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Abstract ：
In this paper, we accomplish the unified convergence analysis of a second-order method of multipliers (i.e., a second-order augmented Lagrangian method) for solving the conventional nonlinear conic optimization problems. Specifically, the algorithm that we investigate incorporates a specially designed nonsmooth (generalized) Newton step to furnish a second-order update rule for the multipliers. We first show in a unified fashion that under a few abstract assumptions, the proposed method is locally convergent and possesses a (nonasymptotic) superlinear convergence rate, even though the penalty parameter is fixed and/or the strict complementarity fails. Subsequently, we demonstrate that for the three typical scenarios, i.e., the classic nonlinear programming, the nonlinear second-order cone programming and the nonlinear semidefinite programming, these abstract assumptions are nothing but exactly the implications of the iconic sufficient conditions that are assumed for establishing the Q-linear convergence rates of the method of multipliers without assuming the strict complementarity.
Keyword ：
second-order method of multipliers second-order method of multipliers semidefinite programming semidefinite programming augmented Lagrangian method augmented Lagrangian method convergence rate convergence rate second-order cone programming second-order cone programming generalized Newton method generalized Newton method
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| GB/T 7714 | Chen, Liang , Zhu, Junyuan , Zhao, Xinyuan . Unified convergence analysis of a second-order method of multipliers for nonlinear conic programming [J]. | SCIENCE CHINA-MATHEMATICS , 2022 , 65 (11) : 2397-2422 . |
| MLA | Chen, Liang 等. "Unified convergence analysis of a second-order method of multipliers for nonlinear conic programming" . | SCIENCE CHINA-MATHEMATICS 65 . 11 (2022) : 2397-2422 . |
| APA | Chen, Liang , Zhu, Junyuan , Zhao, Xinyuan . Unified convergence analysis of a second-order method of multipliers for nonlinear conic programming . | SCIENCE CHINA-MATHEMATICS , 2022 , 65 (11) , 2397-2422 . |
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Abstract ：
In this paper, we show that the quadratic assignment problem (QAP) can be reformulated to an equivalent rank constrained doubly nonnegative (DNN) problem. Under the framework of the difference of convex functions (DC) approach, a semi-proximal DC algorithm is proposed for solving the relaxation of the rank constrained DNN problem whose subproblems can be solved by the semi-proximal augmented Lagrangian method. We show that the generated sequence converges to a stationary point of the corresponding DC problem, which is feasible to the rank constrained DNN problem under some suitable assumptions. Moreover, numerical experiments demonstrate that for most QAP instances, the proposed approach can find the global optimal solutions efficiently, and for others, the proposed algorithm is able to provide good feasible solutions in a reasonable time. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature.
Keyword ：
Functions Functions Constrained optimization Constrained optimization Combinatorial optimization Combinatorial optimization Lagrange multipliers Lagrange multipliers
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| GB/T 7714 | Jiang, Zhuoxuan , Zhao, Xinyuan , Ding, Chao . A proximal DC approach for quadratic assignment problem [J]. | Computational Optimization and Applications , 2021 , 78 (3) : 825-851 . |
| MLA | Jiang, Zhuoxuan 等. "A proximal DC approach for quadratic assignment problem" . | Computational Optimization and Applications 78 . 3 (2021) : 825-851 . |
| APA | Jiang, Zhuoxuan , Zhao, Xinyuan , Ding, Chao . A proximal DC approach for quadratic assignment problem . | Computational Optimization and Applications , 2021 , 78 (3) , 825-851 . |
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Abstract ：
It is well-known that second-order optimizer can accelerate the training of deep neural networks, however, the huge computation cost of second-order optimization makes it impractical to apply in real practice. In order to reduce the cost, many methods have been proposed to approximate a second-order matrix. Inspired by KFAC, we propose a novel Trace-based Hardware-driven layer-ORiented Natural Gradient Descent Computation method, called THOR, to make the second-order optimization applicable in the real application models. Specifically, we gradually increase the update interval and use the matrix trace to determine which blocks of Fisher Information Matrix (FIM) need to be updated. Moreover, by resorting the power of hardware, we have designed a hardware-driven approximation method for computing FIM to achieve better performance. To demonstrate the effectiveness of THOR, we have conducted extensive experiments. The results show that training ResNet-50 on ImageNet with THOR only takes 66.7 minutes to achieve a top-1 accuracy of 75.9 % under an 8 Ascend 910 environment with MindSpore, a new deep learning computing framework. Moreover, with more computational resources, THOR can only takes 2.7 minutes to 75.9 % with 256 Ascend 910.
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| GB/T 7714 | Chen, Mengyun , Gao, Kaixin , Liu, Xiaolei et al. THOR, Trace-Based Hardware-Driven Layer-Oriented Natural Gradient Descent Computation [C] . 2021 : 7046-7054 . |
| MLA | Chen, Mengyun et al. "THOR, Trace-Based Hardware-Driven Layer-Oriented Natural Gradient Descent Computation" . (2021) : 7046-7054 . |
| APA | Chen, Mengyun , Gao, Kaixin , Liu, Xiaolei , Wang, Zidong , Ni, Ningxi , Zhang, Qian et al. THOR, Trace-Based Hardware-Driven Layer-Oriented Natural Gradient Descent Computation . (2021) : 7046-7054 . |
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Abstract ：
Euclidean embedding from noisy observations containing outlier errors is an important and challenging problem in statistics and machine learning. Many existing methods would struggle with outliers due to a lack of detection ability. In this paper, we propose a matrix optimization based embedding model that can produce reliable embeddings and identify the outliers jointly. We show that the estimators obtained by the proposed method satisfy a non-asymptotic risk bound, implying that the model provides a high accuracy estimator with high probability when the order of the sample size is roughly the degree of freedom up to a logarithmic factor. Moreover, we show that under some mild conditions, the proposed model also can identify the outliers without any prior information with high probability. Finally, numerical experiments demonstrate that the matrix optimization-based model can produce configurations of high quality and successfully identify outliers even for large networks.
Keyword ：
Error bound Error bound Euclidean embedding Euclidean embedding Low-rank matrix Low-rank matrix Matrix optimizationg Matrix optimizationg Outliers Outliers
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| GB/T 7714 | Zhang, Qian , Zhao, Xinyuan , Ding, Chao . Matrix optimization based Euclidean embedding with outliers [J]. | COMPUTATIONAL OPTIMIZATION AND APPLICATIONS , 2021 , 79 (2) : 235-271 . |
| MLA | Zhang, Qian et al. "Matrix optimization based Euclidean embedding with outliers" . | COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 79 . 2 (2021) : 235-271 . |
| APA | Zhang, Qian , Zhao, Xinyuan , Ding, Chao . Matrix optimization based Euclidean embedding with outliers . | COMPUTATIONAL OPTIMIZATION AND APPLICATIONS , 2021 , 79 (2) , 235-271 . |
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Abstract ：
Chromatography and mass spectrometry (MS) techniques have greatly improved the power of proteomic analyses. However, sample processing methods used prior to MS, including protein extraction and digestion, remain bottlenecks in the large-scale clinical application of proteomics. Ionic liquids, composed entirely of ions, have high solubility in various solvents. In this study, the effects of the cationic surfactant 1-dodecyl-3-methylimidazolium chloride (C12Im-Cl) on protein digestion were evaluated for clinical proteomic applications. C12Im-Cl was compatible with trypsin and reduced the protein digestion time from 16 h to 1 h. Residual C12Im-Cl was easily removed with a strong anion exchange membrane before MS. We evaluated the performance of C12Im-Cl extraction and rapid protein digestion using formalin-fixed paraffin-embedded liver cancer tissues. The number of proteins and peptides identified was nearly equal to that identified by the traditional filter-aided sample preparation method (2705 vs. 2739 and 16 682 vs. 17 214). In general, the C12Im-Cl-aided rapid sample preparation method is promising for proteomic applications.
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| GB/T 7714 | Liu Chang , Si Xiaoxia , Yan Shumei et al. Development of the C12Im-Cl-assisted method for rapid sample preparation in proteomic application. [J]. | Analytical methods : advancing methods and applications , 2021 , 13 (6) : 776-781 . |
| MLA | Liu Chang et al. "Development of the C12Im-Cl-assisted method for rapid sample preparation in proteomic application." . | Analytical methods : advancing methods and applications 13 . 6 (2021) : 776-781 . |
| APA | Liu Chang , Si Xiaoxia , Yan Shumei , Zhao Xinyuan , Qian Xiaohong , Ying Wantao et al. Development of the C12Im-Cl-assisted method for rapid sample preparation in proteomic application. . | Analytical methods : advancing methods and applications , 2021 , 13 (6) , 776-781 . |
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Abstract ：
In this paper, we conduct a convergence rate analysis of the augmented Lagrangian method with a practical relative error criterion designed in Eckstein and Silva [Mathematical Programming, 141, 319 348 (2013)] for convex nonlinear programming problems. We show that under a mild local error bound condition, this method admits locally a Q-linear rate of convergence. More importantly, we show that the modulus of the convergence rate is inversely proportional to the penalty parameter. That is, an asymptotically superlinear convergence is obtained if the penalty parameter used in the algorithm is increasing to infinity, or an arbitrarily Q-linear rate of convergence can be guaranteed if the penalty parameter is fixed but it is sufficiently large. Besides, as a byproduct, the convergence, as well as the convergence rate, of the distance from the primal sequence to the solution set of the problem is obtained.
Keyword ：
convergence rate convergence rate relative error criterion relative error criterion Augmented Lagrangian method Augmented Lagrangian method
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| GB/T 7714 | Zhao, Xin-Yuan , Chen, Liang . The Linear and Asymptotically Superlinear Convergence Rates of the Augmented Lagrangian Method with a Practical Relative Error Criterion [J]. | ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH , 2020 , 37 (4) . |
| MLA | Zhao, Xin-Yuan et al. "The Linear and Asymptotically Superlinear Convergence Rates of the Augmented Lagrangian Method with a Practical Relative Error Criterion" . | ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH 37 . 4 (2020) . |
| APA | Zhao, Xin-Yuan , Chen, Liang . The Linear and Asymptotically Superlinear Convergence Rates of the Augmented Lagrangian Method with a Practical Relative Error Criterion . | ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH , 2020 , 37 (4) . |
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Abstract ：
Core fucosylation (CF) is a special form of N-glycosylation and plays an important role in pathological and biological processes. Increasing efforts in this area are focused on the identification of CF glycosites, whereas evidence showed that the stoichiometry of CF occupancy is functionally important. Here, an integrated strategy based on "Glycan-Simplification and Paired-Peaks-extraction" (GSPPE) for detecting large-scale stoichiometries of CF was developed. After HILIC enrichment of intact glycopeptides, sequential cleavages by endoglycosidases H and endoglycosidases F3 were performed to generate simplified glycopeptide forms (SGFs), i.e., peptide-GlcNAc (pep-HN) and peptide-GlcNAc-Fucose (pep-CF). These paired SGFs were found to be eluted consecutively on a reversed-phase chromatography column, which allowed us to obtain peak areas of SGF pairs, even if only one of the peaks was captured by the mass spectrometer (MS), by introducing the Paired-Peaks-Extraction algorithm. Thus, the missing value dilemma of random data-dependent MS/MS acquisition was reduced and the stoichiometry of site-specific CF could be calculated. We systematically evaluated the feasibility of this strategy using standard glycoproteins and then explored urinary samples from healthy individuals and hepatocellular carcinoma (HCC) patients. In total, 1449 highly reliable core fucose glycosites and their corresponding CF stoichiometries were obtained. Dozens of glycosites that differed significantly in the urine of healthy individuals and HCC patients were disclosed. The developed approach and program presented here may promote studies on core fucosylation and lead to a deeper understanding of their dysregulation in physiological- or pathological processes.
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| GB/T 7714 | Zhao, Xinyuan , Yu, Zixiang , Huang, Yi et al. Integrated Strategy for Large-Scale Investigation on Protein Core Fucosylation Stoichiometry Based on Glycan-Simplification and Paired-Peaks-Extraction [J]. | ANALYTICAL CHEMISTRY , 2020 , 92 (4) : 2896-2901 . |
| MLA | Zhao, Xinyuan et al. "Integrated Strategy for Large-Scale Investigation on Protein Core Fucosylation Stoichiometry Based on Glycan-Simplification and Paired-Peaks-Extraction" . | ANALYTICAL CHEMISTRY 92 . 4 (2020) : 2896-2901 . |
| APA | Zhao, Xinyuan , Yu, Zixiang , Huang, Yi , Liu, Chang , Wang, Mingchao , Li, Xiaoyu et al. Integrated Strategy for Large-Scale Investigation on Protein Core Fucosylation Stoichiometry Based on Glycan-Simplification and Paired-Peaks-Extraction . | ANALYTICAL CHEMISTRY , 2020 , 92 (4) , 2896-2901 . |
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Abstract ：
Glycan modification prompts important concerns about the quality control of biopharmaceutical production. Conbercept is a multiglycosylated recombinant fusion protein drug approved for the treatment of age-related macular degeneration (AMD). With 14 N-glycosites in the molecule and 7 N-glycosites in the monomer, the charge isomer separation and characterization of conbercept pose great challenges due to its enormous heterogeneities. The batch-to-batch stability on the charge isomer distribution and the possible causation of the pattern necessitate the development of effective analytical approaches. Here, the immobilized pH gradient (IPG)-based two-dimensional gel electrophoresis (2-DE) approach was first optimized to achieve high-resolution, high-reproducible separation and preparation of charge isomers. Then, combined with the quantitative analysis strategy of site-specific N-glycan heterogeneity based on the diagnostic MS2 ion (peptides+GlcNAc, Y1 ions) of glycopeptides, an integrated approach for the quantitation of site-specific N-glycan heterogeneities among charge isomers was established. Finally, the quantitation of site-specific N-glycoforms in each of the 2-DE resolved spots were performed, and the results showed that the sialylation tends to increase for gel spots located in the acidic regions. This study provides an effective approach to separate the charge isomers of the heavily glycosylated protein drugs, and to quantitatively explore the site-specific N-glycans dynamics along with the different charge isomers.
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| GB/T 7714 | Li, Xiaoyu , He, Qing , Yu, Zixiang et al. Site-Specific and Quantitative N-Glycan Heterogeneity Analysis of the Charge Isomers of an Anti-VEGF Recombinant Fusion Protein by High-Resolution Two-Dimensional Gel Electrophoresis and Mass Spectrometry [J]. | ANALYTICAL CHEMISTRY , 2020 , 92 (8) : 5695-5700 . |
| MLA | Li, Xiaoyu et al. "Site-Specific and Quantitative N-Glycan Heterogeneity Analysis of the Charge Isomers of an Anti-VEGF Recombinant Fusion Protein by High-Resolution Two-Dimensional Gel Electrophoresis and Mass Spectrometry" . | ANALYTICAL CHEMISTRY 92 . 8 (2020) : 5695-5700 . |
| APA | Li, Xiaoyu , He, Qing , Yu, Zixiang , Xie, Yuping , Zhao, Xinyuan , Huang, Yi et al. Site-Specific and Quantitative N-Glycan Heterogeneity Analysis of the Charge Isomers of an Anti-VEGF Recombinant Fusion Protein by High-Resolution Two-Dimensional Gel Electrophoresis and Mass Spectrometry . | ANALYTICAL CHEMISTRY , 2020 , 92 (8) , 5695-5700 . |
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Abstract ：
Protein O-glycosylation has long been recognized to be closely associated with many diseases, particularly with tumor proliferation, invasion, and metastasis. The ability to efficiently profile the variation of O-glycosylation in large-scale clinical samples provides an important approach for the development of biomarkers for cancer diagnosis and for therapeutic response evaluation. Therefore, mass spectrometry (MS)-based techniques for high throughput, in-depth and reliable elucidation of protein O-glycosylation in large clinical cohorts are in high demand. However, the wide existence of serine and threonine residues in the proteome and the tens of mammalian O-glycan types lead to extremely large searching space composed of millions of theoretical combinations of peptides and O-glycans for intact O-glycopeptide database searching. As a result, an exceptionally long time is required for database searching, which is a major obstacle in O-glycoproteome studies of large clinical cohorts. More importantly, because of the low abundance and poor ionization of intact O-glycopeptides and the stochastic nature of data-dependent MS2 acquisition, substantially elevated missing data levels are inevitable as the sample number increases, which undermines the quantitative comparison across samples. Therefore, we report a new MS data processing strategy that integrates glycoform-specific database searching, reference library-based MS1 feature matching and MS2 identification propagation for fast identification, in-depth, and reproducible label-free quantification of O-glycosylation of human urinary proteins. This strategy increases the database searching speeds by up to 20-fold and leads to a 30%-40% enhanced intact O-glycopeptide quantification in individual samples with an obviously improved reproducibility. In total, we identified 1300 intact O-glycopeptides in 36 healthy human urine samples with a 30%-40% reduction in the amount of missing data. This is currently the largest dataset of urinary O-glycoproteome and demonstrates the application potential of this new strategy in large-scale clinical investigations.
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| GB/T 7714 | Zhao, Xinyuan , Zheng, Shanshan , Li, Yuanyuan et al. An Integrated Mass Spectroscopy Data Processing Strategy for Fast Identification, In-Depth, and Reproducible Quantification of Protein O-Glycosylation in a Large Cohort of Human Urine Samples [J]. | ANALYTICAL CHEMISTRY , 2020 , 92 (1) : 690-698 . |
| MLA | Zhao, Xinyuan et al. "An Integrated Mass Spectroscopy Data Processing Strategy for Fast Identification, In-Depth, and Reproducible Quantification of Protein O-Glycosylation in a Large Cohort of Human Urine Samples" . | ANALYTICAL CHEMISTRY 92 . 1 (2020) : 690-698 . |
| APA | Zhao, Xinyuan , Zheng, Shanshan , Li, Yuanyuan , Huang, Junjie , Zhang, Wanjun , Xie, Yuping et al. An Integrated Mass Spectroscopy Data Processing Strategy for Fast Identification, In-Depth, and Reproducible Quantification of Protein O-Glycosylation in a Large Cohort of Human Urine Samples . | ANALYTICAL CHEMISTRY , 2020 , 92 (1) , 690-698 . |
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Abstract ：
Sdpnal+ is a MATLAB software package that implements an augmented Lagrangian based method to solve large scale semidefinite programming problems with bound constraints. The implementation was initially based on a majorized semismooth Newton-CG augmented Lagrangian method, here we designed it within an inexact symmetric Gauss-Seidel based semi-proximal ADMM/ALM (alternating direction method of multipliers/augmented Lagrangian method) framework for the purpose of deriving simpler stopping conditions and closing the gap between the practical implementation of the algorithm and the theoretical algorithm. The basic code is written in MATLAB, but some subroutines in C language are incorporated via Mex files. We also design a convenient interface for users to input their SDP models into the solver. Numerous problems arising from combinatorial optimization and binary integer quadratic programming problems have been tested to evaluate the performance of the solver. Extensive numerical experiments conducted in [L.Q. Yang, D.F. Sun, and K.C. Toh, SDPNAL+: A majorized semismooth Newton-CG augmented Lagrangian method for semidefinite programming with nonnegative constraints, Math. Program. Comput. 7 (2015), pp. 331-366] show that the proposed method is quite efficient and robust, in that it is able to solve 98.9% of the 745 test instances of SDP problems arising from various applications to the accuracy of in the relative KKT residual.
Keyword ：
semismooth Newton-CG method semismooth Newton-CG method Matlab software package Matlab software package augmented Lagrangian augmented Lagrangian Semidefinite programming Semidefinite programming
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| GB/T 7714 | Sun, Defeng , Toh, Kim-Chuan , Yuan, Yancheng et al. SDPNAL plus : A Matlab software for semidefinite programming with bound constraints (version 1.0) [J]. | OPTIMIZATION METHODS & SOFTWARE , 2020 , 35 (1) : 87-115 . |
| MLA | Sun, Defeng et al. "SDPNAL plus : A Matlab software for semidefinite programming with bound constraints (version 1.0)" . | OPTIMIZATION METHODS & SOFTWARE 35 . 1 (2020) : 87-115 . |
| APA | Sun, Defeng , Toh, Kim-Chuan , Yuan, Yancheng , Zhao, Xin-Yuan . SDPNAL plus : A Matlab software for semidefinite programming with bound constraints (version 1.0) . | OPTIMIZATION METHODS & SOFTWARE , 2020 , 35 (1) , 87-115 . |
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