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相关概念视频

Introduction to Learning01:18

Introduction to Learning

370
Learning is the process of acquiring knowledge or skills through practice or experience, leading to long-lasting behavioral changes. This acquisition occurs through interaction with the environment and requires practice or experience. For instance, mastering a skill such as surfing requires considerable practice and experience, highlighting the essential role of repeated interactions with the environment in learning.
In contrast to learned behaviors, unlearned behaviors such as crying, sexual...
370
Observational Learning01:12

Observational Learning

166
Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
166
Purposive Learning01:22

Purposive Learning

118
E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a...
118
Cognitive Learning01:21

Cognitive Learning

238
Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
238
Associative Learning01:27

Associative Learning

344
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
344
Visual System01:26

Visual System

574
Light enters the eye through the cornea, a transparent, dome-shaped surface covering the surface of the eyeball that helps to direct and focus incoming light. This light is then channeled toward the pupil, an adjustable opening whose size is controlled by the iris. The iris, a pigmented muscle, regulates the amount of light entering the eye by contracting or dilating the pupil, thereby ensuring optimal light levels for clear vision.
Once through the pupil, the light passes through the lens, a...
574

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EfficientTrain++:通用课程学习,以实现高效的视觉骨干培训

Yulin Wang, Yang Yue, Rui Lu

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    这项研究介绍了EfficientTrain++,一种新的课程学习方法,通过在所有数据中逐渐暴露更容易更难的模式来加速计算机视觉模型训练. 这种方法可以显著减少训练时间,但不会影响准确性.

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    科学领域:

    • 计算机视觉 计算机视觉
    • 机器学习 机器学习
    • 深度学习 (Deep Learning) 是一种深度学习.

    背景情况:

    • 现代计算机视觉骨干实现了高性能,但需要昂贵的培训.
    • 课程学习通常涉及使用更容易更难的数据样本进行培训.

    研究的目的:

    • 将课程学习概括为软选择函数,通过将其重新制定为软选择函数,以发现示例中的模式.
    • 为了减少计算机视觉模型的计算昂贵的训练时间.

    主要方法:

    • 提出了一个课程学习方法,在每个阶段使用所有训练数据,最初专注于更容易的模式.
    • 通过对低频组件的福里埃频谱输入进行切割和调节数据增强强度来实现这一点.
    • 开发了针对课程学习时间表和高效部署技术的定制搜索算法.

    主要成果:

    • EfficientTrain++可以减少各种模型 (ResNet,ConvNeXt,DeiT,PVT,Swin,CSWin,CAFormer) 的训练时间,通过在ImageNet-1 K/22 K上的[公式:参见文本] K.
    • 该方法在不牺牲模型准确性的情况下实现了这种减少.
    • 在自我监督的学习任务中表现出有效性,例如蒙面自动编码器 (MAE).

    结论:

    • EfficientTrain++为加速计算机视觉模型培训提供了一个简单,通用和有效的解决方案.
    • 该方法通过关注数据中的模式难度,成功地将课程学习概括起来.
    • 该方法为优化各种深度学习模型培训提供了一种实用且有效的方法.