Word learning biases are certain biases or assumptions that allow children to quickly rule out unlikely alternatives in order to effectively process and...

of three main lexical constraints, or word learning biases, that are believed to play major roles in word learning, the other two being the whole-object...

unaltered training data. Furthermore, word embeddings can even amplify these biases . Embedding (machine learning) Brown clustering Distributional–relational...

privacy violations to reinforcing social biases of race, gender, sexuality, and ethnicity. The study of algorithmic bias is most concerned with algorithms that...

primacy in persuasion Learning curve List of memory biases List of cognitive biases Nostalgia Outcome primacy Principles of learning Peak–end rule Reminiscence...

This requires the learning algorithm to generalize from the training data to unseen situations in a reasonable way (see inductive bias). This statistical...

Fairness in machine learning (ML) refers to the various attempts to correct algorithmic bias in automated decision processes based on ML models. Decisions...

reality of most of these biases is confirmed by reproducible research, there are often controversies about how to classify these biases or how to explain them...

Biases can be innate or learned. People may develop biases for or against an individual, a group, or a belief. In science and engineering, a bias is...

domain-general perspectives do not dismiss the notion of biases. Rather, they suggest biases develop through learning strategies instead of existing as built-in constraints...

negativity bias has been investigated within many different domains, including the formation of impressions and general evaluations; attention, learning, and...

ISBN 9780080430768. Billman, Dorrit (1996). Structural Biases in Concept Learning. Psychology of Learning and Motivation. Vol. 35. pp. 283–321. doi:10...

In machine learning (ML), feature learning or representation learning is a set of techniques that allow a system to automatically discover the representations...

measured, then a biased sample can still be a reasonable estimate. The word bias has a strong negative connotation. Indeed, biases sometimes come from...

Attention is a machine learning method that determines the importance of each component in a sequence relative to the other components in that sequence...

inherent in human language corpora, but they also inherit inaccuracies and biases present in the data they are trained in. Before 2017, there were a few language...

abstraction. The word "deep" in "deep learning" refers to the number of layers through which the data is transformed. More precisely, deep learning systems have...

Jason D.; Hu, Wei (2023). "Dichotomy of Early and Late Phase Implicit Biases Can Provably Induce Grokking". arXiv:2311.18817 [cs.LG]. Chizat, Lenaic;...

categories of context biases: model-based biases, and frequency-dependent biases. Model-based biases result when an individual is biased to choose a particular...

Active learning is "a method of learning in which students are actively or experientially involved in the learning process and where there are different...

In many languages, the notion of what constitutes a "word" may be learned as part of learning the writing system. This is the case for the English language...

covert censorship, biases the media in some countries, for example China, North Korea, Syria and Myanmar. Politics and media bias may interact with each...

dissonance Confabulation Confirmation bias Decision making Escalation of commitment List of cognitive biases List of memory biases Wishful thinking Lind, Martina;...

a deliberate sense-making process. 3. Surprise biases this process ( the malleability of hindsight bias) by enhancing the recall of surprise-congruent...

representativeness can lead to the model learning and perpetuating societal biases. These inherited biases become especially critical when the ANNs are...

first identified this cognitive bias in their 1979 paper, "Egocentric Biases in Availability and Attribution". Egocentric bias is referred to by most psychologists...

every feature of their language without innate language-specific cognitive biases. Arguments from the poverty of the stimulus are used as evidence for universal...

Jennifer; Smolensky, Paul; Legendre, Géraldine (March 2012). "Learning biases predict a word order universal". Cognition. 122 (3): 306–329. doi:10.1016/j...

selective attention and confirmation bias. The main cause behind frequency illusion, and other related illusions and biases, seems to be selective attention...

Multimodal learning is a type of deep learning that integrates and processes multiple types of data, referred to as modalities, such as text, audio, images...