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丛书名： Engineering applications of Computational Methods

1000年

作者： Chih-Yung Wen Lisong Shi Yazhong Jiang

A data-driven line search rule for support recovery in high-dimensional data analysis

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arXiv 2021年

作者： Li, Peili Jiao, Yuling Lu, Xiliang Kang, Lican School of Statistics Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE East China Normal University Shanghai200062 China School of Mathematics and Statistics Hubei Key Laboratory of Computational Science Wuhan University Wuhan430072 China School of Mathematics and Statistics Wuhan University Wuhan430072 China

In this work, we consider the algorithm to the (nonlinear) regression problems with 0penalty. The existing algorithms for 0based optimization problem are often carried out with a fixed step size, and the selection of an appropriate step size depends on the restricted strong convexity and smoothness for the loss function, hence it is difficult to compute in practical calculation. In sprite of the ideas of support detection and root finding Huang et al. (2021), we proposes a novel and efficient data-driven line search rule to adaptively determine the appropriate step size. We prove the 2error bound to the proposed algorithm without much restrictions for the cost functional. A large number of numerical comparisons with state-of-the-art algorithms in linear and logistic regression problems show the stability, effectiveness and superiority of the proposed algorithms. Copyright © 2021, The Authors. All rights reserved.

关键词： Machine learning

Two applications of Fourier Transform for Lévy Measures On Rp

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SSRN

SSRN 2023年

作者： Qiu, Rui Li, Lu Yin, Xiangrong Yu, Zhou School of Statistics East China Normal University Shanghai200062 China Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE Shanghai200062 China Department of Statistics University of Kentucky LexingtonKY40536-0082 United States

For univariate variable x ∈ R, the Lévy measures for the two real-valued continuous negative definite functions ln and lncosh(x) are shown in Böttcher et al. (2018). In this note, by utilizing the Fourier transform, we present the corresponding Lévy measures for ln and lncosh(|x|) with x ∈ Rp. These Lévy measures have significant potential applications across various domains. © 2023, The Authors. All rights reserved.

关键词： Fourier transforms

DYNAMIC-LLAVA: EFFICIENT MULTIMODAL LARGE LANGUAGE MODELS VIA DYNAMIC VISION-LANGUAGE CONTEXT SPARSIFICATION

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arXiv 2024年

作者： Huang, Wenxuan Zhai, Zijie Shen, Yunhang Cao, Shaosheng Zhao, Fei Xu, Xiangfeng Ye, Zheyu Hu, Yao Lin, Shaohui East China Normal University China Xiamen University China Xiaohongshu Inc China Nanjing University China Key Laboratory of Advanced Theory and Application in Statistics and Data Science MOE China

Multimodal Large Language Models (MLLMs) have achieved remarkable success in vision understanding, reasoning, and interaction. However, the inference computation and memory increase progressively with the generation of output tokens during decoding, directly affecting the efficacy of MLLMs. Existing methods attempt to reduce the vision context redundancy to achieve efficient MLLMs. Unfortunately, the efficiency benefits of the vision context reduction in the prefill stage gradually diminish during the decoding stage. To address this problem, we proposed a dynamic vision-language context sparsification framework Dynamic-LLaVA, which dynamically reduces the redundancy of vision context in the prefill stage and decreases the memory and computation overhead of the generated language context during decoding. Dynamic-LLaVA designs a tailored sparsification inference scheme for different inference modes, i.e., prefill, decoding with and without KV cache, to achieve efficient inference of MLLMs. In practice, Dynamic-LLaVA can reduce computation consumption by ∼75% in the prefill stage. Meanwhile, throughout the entire generation process of MLLMs, Dynamic-LLaVA reduces the ∼50% computation consumption under decoding without KV cache, while saving ∼50% GPU memory overhead when decoding with KV cache, due to the vision-language context sparsification. Extensive experiments also demonstrate that Dynamic-LLaVA achieves efficient inference for MLLMs with negligible understanding and generation ability degradation or even performance gains compared to the full-context inference baselines. Code is available at https://***/Osilly/dynamic_llava . Copyright © 2024, The Authors. All rights reserved.

关键词： Decoding

Studentized permutation method for comparing restricted mean survival times with small sample from randomized trials

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arXiv 2021年

作者： Ditzhaus, Marc Yu, Menggang Xu, Jin Department of Statistics TU Dortmund University Germany Department of Biostatistics and Medical Informatics University of Wisconsin MadisonWI United States Key Laboratory of Advanced Theory and Application in Statistics and Data Science - MOE and School of Statistics East China Normal University China

Recent observations, especially in cancer immunotherapy clinical trials with time-to-event outcomes, show that the commonly used proportional hazard assumption is often not justifiable, hampering an appropriate analyse of the data by hazard ratios. An attractive alternative advocated is given by the restricted mean survival time (RMST), which does not rely on any model assumption and can always be interpreted intuitively. As pointed out recently by Horiguchi and Uno (2020a), methods for the RMST based on asymptotic theory suffer from inflated type-I error under small sample sizes. To overcome this problem, they suggested a permutation strategy leading to more convincing results in simulations. However, their proposal requires an exchangeable data set-up between comparison groups which may be limiting in practice. In addition, it is not possible to invert their testing procedure to obtain valid confidence intervals, which can provide more in-depth information. In this paper, we address these limitations by proposing a studentized permutation test as well as the corresponding permutation-based confidence intervals. In our extensive simulation study, we demonstrate the advantage of our new method, especially in situations with relative small sample sizes and unbalanced groups. Finally we illustrate the application of the proposed method by re-analysing data from a recent lung cancer clinical trial. Copyright © 2021, The Authors. All rights reserved.

关键词： Diseases

Intrinsic mechanical behavior of MgAgSb thermoelectric material:An ab initio study

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Journal of Materiomics 2020年第1期6卷 24-32页

作者： Guodong Li Qi An Umut Aydemir Sergey I.Morozov Bo Duan Pengcheng Zhai Qingjie Zhang William A.Goddard Ⅲ Hubei Key Laboratory of Theory and Application of Advanced Materials Mechanics School of ScienceWuhan University of TechnologyWuhan430070China State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of TechnologyWuhan430070China Department of Chemical and Materials Engineering University of Nevada RenoRenoNV89557USA Department of Chemistry Koc UniversitySariyerIstanbul34450Turkey Boron and Advanced Materials Research Center Koc UniversitySariyerIstanbul34450Turkey Department of Computer Simulation and Nanotechnology South Ural State UniversityChelyabinsk454080Russia Materials and Process Simulation Center California Institute of TechnologyPasadenaCA91125USA

α-MgAgSb based thermoelectric(TE)device attracts much attention for its commercial application because it shows an extremely high conversion efficiency of ~8.5% under a temperature difference of 225 ***,the mechanical behavior of α-MgAgSb is another serious consideration for its engineering ***,we apply density functional theory(DFT)simulations to examine the intrinsic mechanical properties of all three MgAgSb phases,including elastic properties,shear-stress-shear-strain relationships,deformation and failure mechanism under ideal shear and biaxial shear *** find that the ideal shear strength of α-MgAgSb is 3.25 GPa along the most plausible(100)<010>slip *** strength is higher than that of β-MgAgSb(0.80 GPa)and lower than that of γ-MgAgSb(3.43 GPa).The failure of α-MgAgSb arises from the stretching and breakage of MgeSb bond α-MgAgSb under pure shear load,while it arises from the softening of MgeAg bond and the breakage of AgeSb bond under biaxial shear *** suggests that the deformation mechanism changes significantly under different loading conditions.

关键词： MgAgSb thermoelectric materials Density functional theory Ideal strength Deformation mechanism

Dynamic Contrastive Knowledge Distillation for Efficient Image Restoration

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arXiv 2024年

作者： Zhou, Yunshuai Qiao, Junbo Liao, Jincheng Li, Wei Li, Simiao Xie, Jiao Shen, Yunhang Hu, Jie Lin, Shaohui East China Normal University Shanghai China Huawei Noah’s Ark Lab China Xiamen University China Key Laboratory of Advanced Theory and Application in Statistics and Data Science - MOE China

Knowledge distillation (KD) is a valuable yet challenging approach that enhances a compact student network by learning from a high-performance but cumbersome teacher model. However, previous KD methods for image restoration overlook the state of the student during the distillation, adopting a fixed solution space that limits the capability of KD. Additionally, relying solely on L1-type loss struggles to leverage the distribution information of images. In this work, we propose a novel dynamic contrastive knowledge distillation (DCKD) framework for image restoration. Specifically, we introduce dynamic contrastive regularization to perceive the student’s learning state and dynamically adjust the distilled solution space using contrastive learning. Additionally, we also propose a distribution mapping module to extract and align the pixel-level category distribution of the teacher and student models. Note that the proposed DCKD is a structure-agnostic distillation framework, which can adapt to different backbones and can be combined with methods that optimize upper-bound constraints to further enhance model performance. Extensive experiments demonstrate that DCKD significantly outperforms the state-of-the-art KD methods across various image restoration tasks and backbones. Our codes are available at https://***/super-SSS/DCKD. Copyright © 2024, The Authors. All rights reserved.

关键词： Contrastive Learning

Abnormal Shrinkage Behavior and Sintering Mechanism of Alumina Nanoparticles

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SSRN

SSRN 2024年

作者： Wang, Dangqiang Li, Jun Liu, Lisheng Mei, Hai Zhang, Jinyong Hubei Key Laboratory of Theory and Application of Advanced Materials Mechanics Wuhan University of Technology Wuhan China State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of Technology Wuhan China

In ultrafast high-temperature sintering process, the green body can be rapidly densified during the heating stage, and many experimental researches prove that sintering temperature and heating rate play an important role. Thus, to further explore the synergistic effect of sintering temperature and heating rate on densification process and reveal the underlying mechanism, equal-sized and unequal-sized alumina nanoparticles are selected to perform molecular dynamic simulations, and sintering behaviors, microstructure evolution, atomic migration and diffusion activation entropy are monitored during heating stages. Results show that high temperature leads to the amorphization of crystal structure of nanoparticles, and fast heating rate retains large sintering driving force at high temperature, making it easier for atoms to cross the migration barrier, thereby, in addition to the enhancement of surface, lattice and interface diffusion, the appearance of viscous flow accelerate the polymerization process of the nanoparticles, leading to two different abnormal shrinkage behaviors. These findings are expected to lay the theoretical foundation for the development and popularization of ultrafast high-temperature sintering (UHS) technology. © 2024, The Authors. All rights reserved.

关键词： Heating rate

Diagnostic Tests Before Modeling Longitudinal Actuarial Data

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arXiv 2023年

作者： Li, Yinhuan Fung, Tsz Chai Peng, Liang Qian, Linyi Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE School of Statistics East China Normal University Shanghai200241 China Department of Risk Management and Insurance Georgia State University AtlantaGA30303 United States

In non-life insurance, it is essential to understand the serial dynamics and dependence structure of the longitudinal insurance data before using them. Existing actuarial literature primarily focuses on modeling, which typically assumes a lack of serial dynamics and a pre-specified dependence structure of claims across multiple years. To fill in the research gap, we develop two diagnostic tests, namely the serial dynamic test and correlation test, to assess the appropriateness of these assumptions and provide justifiable modeling directions. The tests involve the following ingredients: i) computing the change of the cross-sectional estimated parameters under a logistic regression model and the empirical residual correlations of the claim occurrence indicators across time, which serve as the indications to detect serial dynamics;ii) quantifying estimation uncertainty using the randomly weighted bootstrap approach;iii) developing asymptotic theories to construct proper test statistics. The proposed tests are examined by simulated data and applied to two non-life insurance datasets, revealing that the two datasets behave differently. Copyright © 2023, The Authors. All rights reserved.

关键词： Dynamics

Diagnostic Tests Before Modeling Longitudinal Actuarial Data

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SSRN

SSRN 2022年

In non-life insurance, it is essential to understand the serial dynamics and dependence structure of the longitudinal insurance data before using them. Existing actuarial literature primarily focuses on modeling, which typically assumes a lack of serial dynamics and a pre-specified dependence structure of claims across multiple years. To fill in the research gap, we develop two diagnostic tests, namely the serial dynamic test and correlation test, to assess the appropriateness of these assumptions and provide justifiable modeling directions. The tests involve the following ingredients: i) computing the change of cross-sectional estimated model parameters and the empirical residual correlations of the claims across time, which serve as the indications to detect serial dynamics and peculiar serial dependence of claims;ii) quantifying estimation uncertainty using the randomly weighted bootstrap approach;iii) developing asymptotic theories to construct proper test statistics. The proposed tests are examined by simulated data and applied to two non-life insurance datasets, revealing that the two datasets behave differently. © 2022, The Authors. All rights reserved.

关键词： Insurance