Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Associative Learning

Associative Learning

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...

Residuals and Least-Squares Property

Residuals and Least-Squares Property

The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...

Observational Learning

Observational Learning

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...

Real-World Application of Classical Conditioning

Real-World Application of Classical Conditioning

Classical conditioning not only includes the initial pairing of stimuli but also extends to more complex forms, such as higher-order conditioning. Higher-order conditioning involves creating associations beyond the primary conditioned stimulus, resulting in a chain of conditioned responses.
Higher-order, or second-order, conditioning occurs when a neutral stimulus becomes associated with an already established conditioned stimulus through repeated pairings. For instance, if a dog has been...

Purposive Learning

Purposive Learning

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...

Cognitive Learning

Cognitive Learning

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...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Sampling via the aggregation value for data-driven manufacturing.

National science review·2022

Same author

An integrated experimental and theoretical study on the optical properties of uniform hairy noble metal nanoparticles.

Nanoscale·2018

Same author

Autologous bone marrow stromal cell transplantation as a treatment for acute radiation enteritis induced by a moderate dose of radiation in dogs.

Translational research : the journal of laboratory and clinical medicine·2016

Same author

Angle Insensitive Color Filters in Transmission Covering the Visible Region.

Scientific reports·2016

Same author

Feasibility and acceptability of smartphone applications for seizure self-management in China: Questionnaire study among people with epilepsy.

Epilepsy & behavior : E&B·2016

Same author

Graphene Oxide Papers Simultaneously Doped with Mg(2+) and Cl(-) for Exceptional Mechanical, Electrical, and Dielectric Properties.

ACS applied materials & interfaces·2016

Same journal

Robust Semiglobal and Global Stabilization for Nonlinear Normal Form Systems by Time-Varying Feedback.

IEEE transactions on cybernetics·2026

Same journal

Adaptive Global Asymptotic Output Stabilization of Uncertain Nonlinear Systems Under Dynamic State/Input Quantization.

IEEE transactions on cybernetics·2026

Same journal

Accelerated Distributed Gradient Tracking for Constrained Aggregative Optimization Over Time-Varying Digraphs.

IEEE transactions on cybernetics·2026

Same journal

Small-Gain-Based Plug-and-Play Distributed Control Framework for DC Microgrids With Decentralized Reconfiguration.

IEEE transactions on cybernetics·2026

Same journal

Prescribed-Time Impulsive Control of High-Order Integrator Systems.

IEEE transactions on cybernetics·2026

Same journal

Relaxed Stability Conditions for Model Predictive Control of Hybrid Dynamical Systems Using Hybrid Recurrent Neural Networks.

IEEE transactions on cybernetics·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Dec 20, 2025

The Attentional Set Shifting Task: A Measure of Cognitive Flexibility in Mice

The Attentional Set Shifting Task: A Measure of Cognitive Flexibility in Mice

Published on: February 4, 2015

Transfer Learning Under Conditional Shift Based on Fuzzy Residual.

Gengxiang Chen, Yingguang Li, Xu Liu

IEEE Transactions on Cybernetics

|May 27, 2020

Summary

This summary is machine-generated.

This study introduces Transfer Learning based on Fuzzy Residual (ResTL) for regression problems with conditional shift. ResTL effectively adapts source models to target domains by preserving data distribution properties.

More Related Videos

New Variations for Strategy Set-shifting in the Rat

New Variations for Strategy Set-shifting in the Rat

Published on: January 23, 2017

Related Experiment Videos

Last Updated: Dec 20, 2025

The Attentional Set Shifting Task: A Measure of Cognitive Flexibility in Mice

The Attentional Set Shifting Task: A Measure of Cognitive Flexibility in Mice

Published on: February 4, 2015

New Variations for Strategy Set-shifting in the Rat

New Variations for Strategy Set-shifting in the Rat

Published on: January 23, 2017

Area of Science:

Machine Learning
Artificial Intelligence
Data Science

Background:

Transfer learning is widely applied, but regression under conditional shift is less explored.
Conditional shift occurs when domains share marginal but not conditional distributions.

Purpose of the Study:

To propose a novel transfer learning framework for regression problems with conditional shift.
To introduce Transfer Learning based on Fuzzy Residual (ResTL) for improved model adaptation.

Main Methods:

ResTL formulates the target model by adding fuzzy residual to a model-agnostic source model.
It reuses antecedent parameters from the source fuzzy system.
Two bias computation methods (ResTL_LS and ResTL_RD) are proposed.

Main Results:

Experiments on toy and real-world datasets demonstrate ResTL's effectiveness.
The method successfully adapts models under conditional shift.

Conclusions:

ResTL offers a robust approach for transfer learning in regression with conditional shift.
Preserving source data distribution properties is key to effective model adaptation.