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

The Representativeness Heuristic02:13

The Representativeness Heuristic

16.2K
The representative heuristic describes a biased way of thinking, in which you unintentionally stereotype someone or something. For example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.
16.2K
Incomplete Dominance01:43

Incomplete Dominance

25.4K
Gregor Mendel's work (1822 - 1884) was primarily focused on pea plants. Through his initial experiments, he determined that every gene in a diploid cell has two variants called alleles inherited from each parent. He suggested that amongst these two alleles, one allele is dominant in character and the other recessive. The combination of alleles determines the phenotype of a gene in an organism.
25.4K
Purposive Learning01:22

Purposive Learning

198
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...
198
Woodward–Hoffmann Selection Rules and Microscopic Reversibility01:34

Woodward–Hoffmann Selection Rules and Microscopic Reversibility

3.3K
Electrocyclic reactions, cycloadditions, and sigmatropic rearrangements are concerted pericyclic reactions that proceed via a cyclic transition state. These reactions are stereospecific and regioselective. The stereochemistry of the products depends on the symmetry characteristics of the interacting orbitals and the reaction conditions. Accordingly, pericyclic reactions are classified as either symmetry-allowed or symmetry-forbidden. Woodward and Hoffmann presented the selection criteria for...
3.3K
Nonconscious Mimicry01:13

Nonconscious Mimicry

4.6K
Nonconscious mimicry occurs when individuals alter their mannerisms to match the behaviors and expressions of those nearby, without intention.
4.6K
Associative Learning01:27

Associative Learning

551
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...
551

You might also read

Related Articles

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

Sort by
Same author

Propagation, detection and correction of errors using the sequence database network.

Briefings in bioinformatics·2022
Same author

Exploring automatic inconsistency detection for literature-based gene ontology annotation.

Bioinformatics (Oxford, England)·2022
Same author

Automatic consistency assurance for literature-based gene ontology annotation.

BMC bioinformatics·2021
Same author

GeneMates: an R package for detecting horizontal gene co-transfer between bacteria using gene-gene associations controlled for population structure.

BMC genomics·2020
Same author

Quality Matters: Biocuration Experts on the Impact of Duplication and Other Data Quality Issues in Biological Databases.

Genomics, proteomics & bioinformatics·2020
Same author

Exploring effective approaches for haplotype block phasing.

BMC bioinformatics·2019

Related Experiment Video

Updated: Sep 4, 2025

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

4.7K

When proxy-driven learning is no better than random: The consequences of representational incompleteness.

Justin Zobel1, Felisa J Vázquez-Abad1,2, Pauline Lin1

  • 1School of Computing & Information Systems, the University of Melbourne, Parkville, Victoria, Australia.

Plos One
|July 13, 2022
PubMed
Summary

Machine learning personalization can fail if systems lack full user understanding. Incomplete data representations mean learning may be random and systems may not realize they are failing.

More Related Videos

The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task
10:39

The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task

Published on: May 3, 2018

8.6K
Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation
06:53

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation

Published on: March 1, 2017

13.3K

Related Experiment Videos

Last Updated: Sep 4, 2025

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

4.7K
The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task
10:39

The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task

Published on: May 3, 2018

8.6K
Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation
06:53

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation

Published on: March 1, 2017

13.3K

Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Human-Computer Interaction

Background:

  • Machine learning personalizes systems by adapting to human responses using quantified features and objective functions.
  • System adaptation relies on accurate world representations and complete proxies for desirable outcomes.

Purpose of the Study:

  • To analyze the impact of incomplete representations in machine learning personalization.
  • To investigate how incomplete proxies affect learning system performance and awareness of failure.

Main Methods:

  • Mathematical analysis of machine learning personalization.
  • Simulations using a reinforcement-learning case study.

Main Results:

  • Incomplete representations can lead to learning performance no better than random.
  • Learning systems may be inherently unaware of their failure due to incomplete proxies.

Conclusions:

  • Incompleteness of representation is a fundamental challenge in machine learning for human-centric domains.
  • Understanding these limitations is crucial for the effective and reliable application of machine learning systems.