Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Associative Learning01:27

Associative Learning

335
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...
335
Thermal Sigmatropic Reactions: Overview01:16

Thermal Sigmatropic Reactions: Overview

2.1K
Sigmatropic rearrangements are a class of pericyclic reactions in which a σ bond migrates from one part of a π system to another. These are intramolecular rearrangements where the total number of σ and π bonds remain unchanged.
Sigmatropic shifts are classified based on an order term [i, j ], where i and j indicate the number of atoms across which each end of the σ bond migrates. Below are examples of a [3,3] sigmatropic shift in...
2.1K
Law of Independent Assortment02:03

Law of Independent Assortment

55.6K
While Mendel’s Law of Segregation states that the two alleles for one gene are separated into different gametes, a different question of how different genes are inherited remains. For example, is the gene for tall plants inherited with the gene for green peas? Mendel asked this question by experimenting with a dihybrid cross; a cross in which both parents are homozygous for two distinct traits resulting in an F1 generation that are heterozygous for both traits.
55.6K
Position-effect Variegation02:32

Position-effect Variegation

6.3K
In 1928, a German botanist Emil Heitz observed the moss nuclei with a DNA binding dye. He observed that while some chromatin regions decondense and spread out in the interphase nucleus, others do not. He termed them euchromatin and heterochromatin, respectively. He proposed that the heterochromatin regions reflect a functionally inactive state of the genome. It was later confirmed that heterochromatin is transcriptionally repressed, and euchromatin is transcriptionally active chromatin.
6.3K
Perceptual Constancy01:12

Perceptual Constancy

382
Perceptual constancy is the ability to recognize that objects remain consistent and unchanged even when their appearance varies due to changes in sensory input. There are four main types of perceptual constancy: size constancy, shape constancy, color constancy, and brightness constancy.
Size constancy is the recognition that an object remains the same size, even when its image on the retina changes. For instance, a bus is perceived to be large enough to carry people, even if it looks tiny from...
382
State Space Representation01:27

State Space Representation

203
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
203

You might also read

Related Articles

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

Sort by
Same author

Open-Set Domain Adaptation via Target-Relaxed Optimal Transport.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same author

CGDock: Curvature-Aware Geometric Flow Framework for Protein-Ligand Docking.

Journal of chemical information and modeling·2026
Same author

Partial Domain Adaptation via Importance Sampling-Based Shift Correction.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2025
Same author

Geometric Understanding of Discriminability and Transferability for Visual Domain Adaptation.

IEEE transactions on pattern analysis and machine intelligence·2024
Same author

Cross-site prognosis prediction for nasopharyngeal carcinoma from incomplete multi-modal data.

Medical image analysis·2024
Same author

BuresNet: Conditional Bures Metric for Transferable Representation Learning.

IEEE transactions on pattern analysis and machine intelligence·2022
Same journal

A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Benchmarking the Robustness of Autonomous Driving to Environmental Illusions: A Lane Perception Perspective.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Learning Topology-Aware Representations via Test-Time Adaptation for Anomaly Segmentation.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

TraGraph-GS: Trajectory Graph-based Gaussian Splatting for Arbitrary Large-Scale Scene Rendering.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

SWIFT: A Small-World Interaction Framework for Flow-Aware Trajectory Prediction in Autonomous Driving.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

HardFlow: Hard-Constrained Sampling for Flow-Matching Models Via Trajectory Optimization.

IEEE transactions on pattern analysis and machine intelligence·2026
See all related articles

Related Experiment Video

Updated: Jun 23, 2025

Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms
07:31

Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms

Published on: February 8, 2019

6.6K

When Invariant Representation Learning Meets Label Shift: Insufficiency and Theoretical Insights.

You-Wei Luo, Chuan-Xian Ren

    IEEE Transactions on Pattern Analysis and Machine Intelligence
    |June 21, 2024
    PubMed
    Summary
    This summary is machine-generated.

    Generalized label shift (GLS) theory addresses changing environments in machine learning. This study proves GLS correction is necessary for generalization, introducing a new kernel embedding-based algorithm (KECA) that outperforms existing methods.

    More Related Videos

    Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine
    07:05

    Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine

    Published on: October 27, 2016

    9.2K
    Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
    05:48

    Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

    Published on: August 9, 2024

    1.5K

    Related Experiment Videos

    Last Updated: Jun 23, 2025

    Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms
    07:31

    Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms

    Published on: February 8, 2019

    6.6K
    Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine
    07:05

    Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine

    Published on: October 27, 2016

    9.2K
    Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
    05:48

    Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

    Published on: August 9, 2024

    1.5K

    Area of Science:

    • Machine Learning
    • Artificial Intelligence
    • Data Science

    Background:

    • Classical machine learning assumes identical data distributions, limiting real-world applicability.
    • Dataset shift and invariant representation learning are studied to address changing environments.
    • Generalized Label Shift (GLS) offers a promising approach for complex distribution shifts.

    Purpose of the Study:

    • To explore limitations in current dataset shift theory and algorithms.
    • To provide a comprehensive understanding of Generalized Label Shift (GLS).
    • To develop novel theoretical insights and a superior correction algorithm for dataset shift.

    Main Methods:

    • Derived two generalization bounds for GLS learners.
    • Proved the sufficiency and necessity of GLS correction for generalization.
    • Proposed a kernel embedding-based correction algorithm (KECA) for knowledge transfer.

    Main Results:

    • Demonstrated the insufficiency of invariant representation learning for complex shifts.
    • Showcased the theoretical sufficiency and necessity of GLS correction.
    • KECA minimized generalization error and achieved successful knowledge transfer.

    Conclusions:

    • GLS correction is essential for building generalizable models under dataset shift.
    • The proposed KECA algorithm offers a superior method for addressing dataset shift.
    • This work provides theoretical and methodological advancements for robust machine learning.