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相关概念视频

Associative Learning01:27

Associative Learning

362
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...
362
Observational Learning01:12

Observational Learning

173
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...
173
Hindsight Biases01:12

Hindsight Biases

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Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Can you relate this to the phrase "Hindsight is 20/20" now? 
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Purposive Learning01:22

Purposive Learning

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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...
121
Cognitive Learning01:21

Cognitive Learning

243
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...
243
Introduction to Learning01:18

Introduction to Learning

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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...
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走向可解释的多方学习:一个对比的知识共享框架

Yuan Gao, Yuanqiao Zhang, Maoguo Gong

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    此摘要是机器生成的。

    这项研究引入了一个新的对比的多方学习框架,以加强从分散数据的知识共享. 这种新的方法通过解决系统和统计异质性挑战来提高模型性能.

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    The Spatial Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition
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    相关实验视频

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    科学领域:

    • 人工智能的人工智能
    • 机器学习 机器学习
    • 分布式系统 分布式系统

    背景情况:

    • 多方学习可以通过分散的数据进行联合模型培训,但面临着系统/统计异质性和激励设计等挑战.
    • 现有的方法在隐私,数据分布依赖性和通信效率方面扎.

    研究的目的:

    • 提出一个新的多方学习框架,以提高知识的精细化和分享效率.
    • 解决传统多方学习的局限性,包括隐私问题和异质性问题.

    主要方法:

    • 开发了一种对比的多方学习框架,模拟人类认知和交流,以共享知识.
    • 引入了一个可追究责任的激励机制,以加强参与.
    • 模拟多方学习作为一个多对一的知识共享问题,避免直接参数平均.

    主要成果:

    • 拟议的框架以透明的方式整合了明确的知识,而无需披露隐私.
    • 在各种场景和现实世界数据集中展示了显著的模型性能改进.
    • 减少对数据分布和通信环境的依赖.

    结论:

    • 这种新的多方学习框架有效地提炼和分享来自分散数据的知识.
    • 该方法为多方学习中的异质性和激励挑战提供了强有力的解决方案.
    • 与现有方法相比,实现了优越的模型性能和效率.