相关实验视频
Updated: Jul 2, 2025

13:19
Deep Neural Networks for Image-Based Dietary Assessment
Published on: March 13, 2021
9.2K
在随机梯度下降的不同模式上
Antonio Sclocchi1, Matthieu Wyart1
1Institute of Physics, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland.
概括
深度学习中的随机梯度下降 (SGD) 动态揭示了由批量大小和学习速度控制的不同阶段. 了解这些阶段对于优化模型概括和培训效率至关重要.
科学领域:
- 机器学习 机器学习
- 深度学习 (Deep Learning) 是一种深度学习.
- 计算神经科学是一种神经科学.
背景情况:
- 深度神经网络通常使用随机梯度下降 (SGD) 进行训练.
- 关键的超参数包括批量大小和学习率,影响培训动态.
- SGD的行为可以通过温度参数来描述,但对于大批量产品来说,这种情况会崩.
研究的目的:
- 了解SGD动态变化的交叉点.
- 分析批量规模和学习率对深度网络培训的影响.
- 为了将这些动态阶段连接到泛化错误.
主要方法:
- 对教师与学生的感知分类模型的分析.
- 在深度网络上进行经验验证.
- 在批量大小-学习速率平面中导出相位图.
主要成果:
- 确定了三个不同的动态阶段:噪声主导的SGD,大第一步主导的SGD和梯度下降 (GD).
- 这些阶段与不同的概括错误模式相关.
- 阶段之间的批量大小值与训练集大小相比,取决于问题的硬度.
结论:
- 该研究提供了SGD的相位图,澄清了它在不同超参数设置中的行为.
- 对SGD动态的洞察力可以指导深度学习模型的优化.
- 这些发现为理解深度网络中的概括提供了一个理论框架.
相关概念视频
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
54
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...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
54
Entropy Change in Reversible Processes
2.5K
In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
2.5K
Randomized Experiments
6.9K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
Simple randomization
Simple...
6.9K
Divergence and Stokes' Theorems
1.6K
The divergence and Stokes' theorems are a variation of Green's theorem in a higher dimension. They are also a generalization of the fundamental theorem of calculus. The divergence theorem and Stokes' theorem are in a way similar to each other; The divergence theorem relates to the dot product of a vector, while Stokes' theorem relates to the curl of a vector. Many applications in physics and engineering make use of the divergence and Stokes' theorems, enabling us to write...
1.6K
Forced Transdifferentiation
1.9K
Transdifferentiation, also known as lineage reprogramming, was first discovered by Selman and Kafatos in 1974 in silkmoths. They observed that the moths’ cuticle-producing cells transformed into salt-producing cells. Many such cases of natural transdifferentiation occur in organisms. In humans, pancreatic alpha cells can become beta cells. In newts, the loss of the eye’s lens causes the pigmented epithelial cells to transdifferentiate into the lens cells.
Artificial...
Artificial...
1.9K
Regression Toward the Mean
6.3K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.3K

