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相关概念视频

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
45
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

439
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
439
Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model01:13

Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model

56
Drugs administered through various routes can lead to nonlinear elimination, resulting in complex pharmacokinetic behaviors crucial to understanding efficacious drug dosing.
When a drug is administered through a constant intravenous infusion and eliminated via nonlinear pharmacokinetics, it follows zero-order input. For example, oral drugs undergo first-order absorption upon administration and are eliminated through nonlinear pharmacokinetics.
In the case of subcutaneously administered drugs,...
56
Statically Indeterminate Problem Solving01:16

Statically Indeterminate Problem Solving

369
Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...
369
Routh-Hurwitz Criterion II01:19

Routh-Hurwitz Criterion II

208
In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first...
208
Routh-Hurwitz Criterion I01:15

Routh-Hurwitz Criterion I

197
Consider an electrical power grid, where stability is essential to prevent blackouts. The Routh-Hurwitz criterion is a valuable tool for assessing system stability under varying load conditions or faults. By analyzing the closed-loop transfer function, the Routh-Hurwitz criterion helps determine whether the system remains stable.
To apply the Routh-Hurwitz criterion, a Routh table is constructed. The table's rows are labeled with powers of the complex frequency variable s, starting from the...
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Deep Neural Networks for Image-Based Dietary Assessment
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非凸的零次随机ADMM方法具有较低的函数查询复杂性.

Feihu Huang, Shangqian Gao, Jian Pei

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    PubMed
    概括
    此摘要是机器生成的。

    零级方法可以解决机器学习的挑战,没有梯度. 新的ZO-SPIDER-ADMM和ZOO-ADMM+算法显著降低了对处罚的非凸问题的函数查询复杂性.

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    科学领域:

    • 优化方法优化方法.
    • 机器学习 机器学习
    • 没有衍生品的优化优化.

    背景情况:

    • 零级方法对于机器学习至关重要,当梯度不可用或昂贵时.
    • 现有的方法存在高函数查询复杂性和局限性,具有复杂的惩罚和约束.

    研究的目的:

    • 开发更快的零顺序方法,解决现有方法的缺点.
    • 用多个不平滑的惩罚来解决非凸的有限和在线问题.

    主要方法:

    • 拟议的零次随机交替方向乘数方法 (ZO-SPIDER-ADMM) 用于有限和问题.
    • 为在线问题开发了零级在线ADMM方法 (ZOO-ADMM+).
    • 证明了对两个拟议方法的函数查询复杂性的改进.

    主要成果:

    • ZO-SPIDER-ADMM实现了对e-静止点的函数查询复杂度为O{\displaystyle O{\displaystyle n} 1/2) ε−2,使现有方法得到了O{\displaystyle O{\displaystyle n} 1/2) 的改进.
    • ZOO-ADMM+ 实现了对 ε-静止点的函数查询复杂度为 O{\displaystyle O{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text}{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text{\text}}}}}}}\text{\text{\text{\text{\text{\text{\text{\text}}}}}}}}}}}}}}.
    • 对深度神经网络的对抗性攻击的实验验证证证了算法效率.

    结论:

    • 拟议的ZO-SPIDER-ADMM和ZOO-ADMM+在函数查询复杂性方面提供了显著的改进,以实现零级优化.
    • 这些新的算法有效地解决了复杂的非凸问题,使用非光滑的惩罚和约束.
    • 这些方法证明了实际的有效性,特别是在对深度学习模型的对抗性攻击场景中.