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相关概念视频

Survival Tree01:19

Survival Tree

105
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
105
Observational Learning01:12

Observational Learning

202
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...
202
Introduction to Learning01:18

Introduction to Learning

460
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...
460
Associative Learning01:27

Associative Learning

428
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...
428
Avoidance Learning and Learned Helplessness01:14

Avoidance Learning and Learned Helplessness

1.8K
Avoidance learning and learned helplessness are critical concepts in understanding behavioral responses to negative stimuli.
Avoidance learning occurs when an organism learns that a specific behavior can prevent an unpleasant outcome. For example, a student who receives a bad grade may start studying harder to avoid future poor grades. This behavior persists even when the negative outcome is no longer present. Avoidance learning is powerful because it maintains behavior in the absence of the...
1.8K
Purposive Learning01:22

Purposive Learning

135
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...
135

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相关实验视频

Updated: Jul 15, 2025

Using a Split-belt Treadmill to Evaluate Generalization of Human Locomotor Adaptation
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Using a Split-belt Treadmill to Evaluate Generalization of Human Locomotor Adaptation

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如何通过后门分割学习.

Fangchao Yu1, Lina Wang1, Bo Zeng1

  • 1Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University, Wuhan, 430072, China.

Neural networks : the official journal of the International Neural Network Society
|October 2, 2023
PubMed
概括
此摘要是机器生成的。

分割学习易受客户端和服务器的后门攻击. 这项研究引入了新的攻击框架,突出了分布式机器学习应用程序的重大安全风险.

关键词:
辅助模型 辅助模型后门攻击后门攻击一个影子模型.分拆学习是指分开学习.

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相关实验视频

Last Updated: Jul 15, 2025

Using a Split-belt Treadmill to Evaluate Generalization of Human Locomotor Adaptation
08:04

Using a Split-belt Treadmill to Evaluate Generalization of Human Locomotor Adaptation

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科学领域:

  • 计算机科学 计算机科学
  • 人工智能的人工智能
  • 机器学习安全 机器学习安全

背景情况:

  • 分拆学习提供了一个灵活的分布式框架,特别是对于资源有限的参与者.
  • 现有的安全研究主要针对分裂学习中的推断攻击.
  • 数据/模型控制与使用权的分离引发了安全问题.

研究的目的:

  • 为了调查和证明分裂学习对后门攻击的脆弱性.
  • 从客户端和服务器的角度提出新的后门攻击框架.
  • 突出潜在的安全风险,并为安全部署分割学习提供信息.

主要方法:

  • 客户端攻击:将后门样本插入到本地训练数据中,使用可适应的标签.
  • 服务器端攻击:操纵客户端模型的优化方向并使用辅助模型.
  • 评估攻击的有效性和对主要任务执行的影响.

主要成果:

  • 在客户端和服务器端的后门攻击中展示了高攻击精度.
  • 表明攻击不会影响主要分类学习任务的执行.
  • 验证了辅助模型在增强后门攻击敏感性的有效性.

结论:

  • 分割学习系统容易受到复杂的后门攻击.
  • 拟议的框架构成重大安全威胁,需要强大的防御机制.
  • 这项工作强调了在分割学习部署中迫切需要加强安全协议的迫切需要.