PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “GENERALIZATION LEARNING”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 523 records · Page 29Linked to original sources
PubMed2006

Learning alters local face space geometry.

The effects of learning on the geometry of face space were investigated by measuring thresholds for discrimination and recognition of synthetic faces. This was based on a novel experimental technique that permitted measurement of psychometric functions for face recognition. Two major results were obtained. First, thresholds for face recognition were significantly better than thresholds for discrimination among novel faces. Second, rapid discrimination in the neighborhood of learned faces was better than discrimination near novel faces. Control experiments showed that this discrimination improvement occurred only with learned faces, and it could not be explained by generalized discrimination learning. Thus, face learning selectively alters or distorts face space in the vicinity of learned faces. This alteration may be due to an improvement in the signal/noise ratio as a result of face learning.

Discrimination, Psychological↗
PubMed2004

Characteristics of learning voluntary control of posture in lesions of the pyramidal and nigrostriatal systems.

The aim of the study reported here was to investigate impairments on the learning of voluntary control of the center of pressures using visual feedback in patients with lesions of the corticospinal and nigrostriatal systems. Participants were 33 patients with Parkinson's disease and 20 patients with hemipareses due to circulatory lesions in the basin of the middle cerebral artery. Subjects stood on a stabilometric platform and used two computer games over 10 days to learn to shift the body relative to the foot to move the centre of pressures, indicated by the position of a cursor on the screen, with the target and to move the target to a specified part of the screen. The games differed in terms of the postural tasks. In one, the direction of movement of the center of pressures was not known to the subjects, and subjects learned a general strategy for posture control; the other formed a strictly defined postural coordination. Both groups of patients were found to have impairments of voluntary control of the position of the center of pressures. There were no differences between groups of patients, in terms of the severity of the initial performance deficit in the task involving shifts of the center of pressures in different directions (the general strategy for controlling the center of pressures), while learning of this task was more difficult for patients with Parkinson's disease. The initial deficit in the fine postural coordination task was more marked in patients with Parkinsonism, though learning in these patients was significantly better than in patients with hemipareses. It is suggested that the mechanisms of involvement of the nigrostriatal and corticospinal systems in learning the voluntary control of posture have elements in common as well as unique elements.

Adult↗
PubMed1997

Fractionating the nonspatial pretraining effect in the water maze task.

Nonspatial pretraining (NSP) enables rats to learn the general strategies of the water maze task (WMT; e.g., learning to swim away from the wall and to climb onto the hidden platform), reduces sensorimotor disturbances, and eliminates acquisition impairments caused by scopolamine hydrobromide, a muscarinic antagonist. To evaluate the contributions of the components of NSP to these effects, NSP was fractionated so that different groups of male rats swam, were placed onto the hidden platform, climbed onto the hidden platform, or were placed into an empty maze before spatial training under scopolamine. No single component of the NSP procedure was sufficient to produce its full effects on sensorimotor disturbances and WMT acquisition. Experience with most or perhaps all of the specific behaviors required in the WMT appears to be important for NSP to produce its full effects.

Animals↗
PubMed2006

Interactions between encoding and retrieval in the domain of sequence-learning.

In this article, the authors propose to characterize sequence learning in terms of automatic versus non-automatic processing and to apply this contrast independently to knowledge acquisition and retrieval. In several experiments of sequence learning, automaticity of both the acquisition and retrieval of the acquired knowledge was independently assessed. It was found that the sequence learning order can be demonstrated under all combinations of knowledge acquisition and retrieval. In particular, at least in the simple sequences the authors used, this applies in cases in which both the acquisition and the retrieval of knowledge are strictly automatic--that is, when neither is required for the task nor beneficial to deliberate behavior. The proposed framework has implications for the notion of sequence learning and the investigation of learning in general.

Association Learning↗
PubMed2003

Schema theory: critical review and implications for the role of cognition in a new theory of motor learning.

This paper is based on a symposium celebrating the 26th anniversary of the publication of "A Schema Theory of Discrete Motor Skill Learning" (Schmidt, 1975) held at the annual conference of the North American Society for the Psychology of Sport and Physical Activity in June 2001. We provide a brief historical context for schema theory and a review of the development of the mechanistic approach to motor learning in general. We explore recent findings in mental practice, observational learning, augmented feedback presentation, and the variability of practice that are inconsistent with schema theory and provide a rationale for the importance of cognitive activity in motor learning.

Child↗
PubMed2005

Relevance feedback using generalized Bayesian framework with region-based optimization learning.

This paper presents a generalized Bayesian framework for relevance feedback in content-based image retrieval. The proposed feedback technique is based on the Bayesian learning method and incorporates a time-varying user model into the formulation. We define the user model with two terms: a target query and a user conception. The target query is aimed to learn the common features from relevant images so as to specify the user's ideal query. The user conception is aimed to learn a parameter set to determine the time-varying matching criterion. Therefore, at each feedback step, the learning process updates not only the target distribution, but also the target query and the matching criterion. In addition, another objective of this paper is to conduct the relevance feedback on images represented in region level. We formulate the matching criterion using a weighting scheme and proposed a region clustering technique to determine the region correspondence between relevant images. With the proposed region clustering technique, we derive a representation in region level to characterize the target query. Experiments demonstrate that the proposed method combined with time-varying user model indeed achieves satisfactory results and our proposed region-based techniques further improve the retrieval accuracy.

Algorithms↗
PubMed1982

Learning disabled children's syntactic proficiency on a communicative task.

Previous studies have generally examined learning disabled children's syntactic ability either on structured tasks or by analyzing oral language samples collected under conditions not typical of natural communicative settings. Thus, these studies are of limited value in exploring the impact of learning disabled children's deficits in linguistic structure on their use of language in social contexts. The purpose of this study was to investigate learning disabled children's syntactic proficiency during a task requiring them to convey information to a listener. Subjects were selected on the bases of teacher ratings, reading achievement scores, and Peabody Picture Vocabulary Test IQ scores within the normal range; those children identified as learning disabled received low ratings and demonstrated underachievement (below 40th percentile for their grade) in reading. Oral language samples were collected by having learning disabled and normally achieving children in grades two, four, six, and eight participate in a referential communication task in which they described abstract shapes to an experimenter. The length and syntactic complexity of the children's descriptions were assessed. Learning disabled children in all grades were found to produce shorter mean t-units and shorter mean main clauses than nondisabled children even on this relatively simple communicative task. Although learning disabled children's linguistic problems have previously been characterized as subtle, these findings suggest that their productive language deficits may be significant enough to interfere with even the informal and elliptical conversations characteristic of communication among peers and family members.

Adolescent↗
PubMed2001

Improvement of generalization ability for identifying dynamical systems by using universal learning networks.

This paper studies how the generalization ability of models of dynamical systems can be improved by taking advantage of the second order derivatives of the outputs with respect to the external inputs. The proposed method can be regarded as a direct implementation of the well-known regularization technique using the higher order derivatives of the Universal Learning Networks (ULNs). ULNs consist of a number of interconnected nodes where the nodes may have any continuously differentiable nonlinear functions in them and each pair of nodes can be connected by multiple branches with arbitrary time delays. A generalized learning algorithm has been derived for the ULNs, in which both the first order derivatives (gradients) and the higher order derivatives are incorporated. First, the method for computing the second order derivatives of ULNs is discussed. Then, a new method for implementing the regularization term is presented. Finally, simulation studies on identification of a nonlinear dynamical system with noises are carried out to demonstrate the effectiveness of the proposed method. Simulation results show that the proposed method can improve the generalization ability of neural networks significantly, especially in terms that (1) the robust network can be obtained even when the branches of trained ULNs are destructed, and (2) the obtained performance does not depend on the initial parameter values.

Computer Simulation↗
PubMed2001

Recognition and categorization of biologically significant objects by rhesus monkeys (Macaca mulatta): the domain of food.

To survive, organisms must be able to identify edible objects. However, we know relatively little about how humans and other species distinguish food items from non-food items. We tested the abilities of semi-free-ranging rhesus monkeys (Macaca mulatta) to learn rapidly that a novel object was edible, and to generalize their learning to other objects, in a spontaneous choice task. Adult monkeys watched as a human experimenter first pretended to eat one of two novel objects and then placed replicas of the objects at widely separated locations. Monkeys selectively approached the object that the experimenter had previously eaten, exhibiting a rapidly induced preference for the apparently edible object. In further experiments in which the same objects were used as tools or were manipulated at the face but not eaten, we fail to observe an approach bias, providing evidence that the monkeys' pattern of approach in the earlier experiments was specific to objects that were eaten. Subsequent experiments tested how monkeys generalized their preference for an edible object by first allowing them to watch a human experimenter eat one of two objects and then presenting them with new objects composed of the same substance but differing from the original, edible object in shape or color. Monkeys ignored changes in the shape of the object and generalized from one edible object to another on the basis of color in conjunction with other substance properties. Finally, we extended this work to infant rhesus monkeys and found that, like adults, they too used color to generalize to novel food objects. In contrast to adults, however, infants extended this pattern of generalization to objects that were acted on in other ways. These results suggest that infant monkeys form broader object categories than adults, and that food categories become sharpened as a function of maturational or experiential factors.

Age Factors↗
PubMed2004

Tree-structured supervised learning and the genetics of hypertension.

This paper is about an algorithm, FlexTree, for general supervised learning. It extends the binary tree-structured approach (Classification and Regression Trees, CART) although it differs greatly in its selection and combination of predictors. It is particularly applicable to assessing interactions: gene by gene and gene by environment as they bear on complex disease. One model for predisposition to complex disease involves many genes. Of them, most are pure noise; each of the values that is not the prevalent genotype for the minority of genes that contribute to the signal carries a "score." Scores add. Individuals with scores above an unknown threshold are predisposed to the disease. For the additive score problem and simulated data, FlexTree has cross-validated risk better than many cutting-edge technologies to which it was compared when small fractions of candidate genes carry the signal. For the model where only a precise list of aberrant genotypes is predisposing, there is not a systematic pattern of absolute superiority; however, overall, FlexTree seems better than the other technologies. We tried the algorithm on data from 563 Chinese women, 206 hypotensive, 357 hypertensive, with information on ethnicity, menopausal status, insulin-resistant status, and 21 loci. FlexTree and Logic Regression appear better than the others in terms of Bayes risk. However, the differences are not significant in the usual statistical sense.

Algorithms↗
PubMed1994

Optimal Hebbian learning rules and the role of asymmetry.

We study the storage properties associated with generalized Hebbian learning rules which present four free parameters that allow for asymmetry. We also introduce two extra parameters in the post-synaptic potentials in order to further improve the critical capacity. Using signal-to-noise analysis, as well as computer simulations on an analog network, we discuss the performance of the rules for arbitrarily biased patterns and find that the critical storage capacity alpha c becomes maximal for a particular symmetric rule (alpha c diverges in the sparse coding limit). Departures from symmetry decrease alpha c but can increase the robustness of the model.

Artificial Intelligence↗
PubMed2003

Global perception in small brains: topological pattern recognition in honey bees.

A series of experiments with honey bees demonstrate that their small brains nevertheless possess the ability for topological perception. Bees rapidly learned to discriminate patterns that are topologically different, and they generalized the learned cue to other novel patterns. By contrast, discrimination of topologically equivalent patterns was learned much more slowly and not as well. Thus, although the global nature of topological properties makes their computation difficult, topology may be a fundamental component of the vocabulary by which visual systems represent and characterize objects.

Animals↗