Results 11 to 20 of about 23,083,115 (240)
Deep Archetypal Analysis [PDF]
, 2019 Deep Archetypal Analysis (DeepAA) generates latent representations of high-dimensional datasets in terms of intuitively understandable basic entities called archetypes.
Maxim Samarin +7 more
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IDEAS Journal on English Language Teaching and Learning Linguistics and Literature, 2020 This study aims at analyzing the representation of women's existence through the archetypal image in the chrysanthemum story. This study uses Carl Jung's archetypal image theory which is supported by Simone de Beauvoir's theoretical concepts.
Desria Natalia Sirait, Tomi Arianto
exaly +3 more sources
Archetypical motion: Supervised game behavior learning with Archetypal Analysis
2013 IEEE Conference on Computational Inteligence in Games (CIG), 2022 8 S.The problem of creating believable game AI poses numerous challenges for computational intelligence research. A particular challenge consists in creating human-like behaving game bots by means of applying machine learning to game-play data recorded ...
Bauckhage, Christian, Sifa, Rafet
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Fast and Robust Archetypal Analysis for Representation Learning [PDF]
, 2014 International audienceWe revisit a pioneer unsupervised learning technique called archetypal analysis, which is related to successful data analysis methods such as sparse coding and non-negative matrix factorization.
Chen, Yuansi +5 more
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Archetypal analysis of interval data
Reliab. Comput., 2010 In this paper we present a mathematical model for archetypal analysis of data represented by means of intervals of real numbers. We extend the model for single-valued data proposed in the pioneering work of Cutler and Breiman on this topic.
Stefania Corsaro +3 more
core +4 more sources
Archetypal analysis for data-driven prototype identification
Statistical Analysis and Data Mining: The ASA Data Science Journal, 2017 Prototypes, as Rosch (1973) defined the term in the cognitive sciences field, are ideal exemplars that summarize and represent groups of objects (or categories) and that are “typical" according to their internal resemblance and external dissimilarity vis-
PALUMBO, FRANCESCO +5 more
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Consistency of Archetypal Analysis
SIAM Journal on Mathematics of Data Science, 2021 Archetypal analysis is an unsupervised learning method that uses a convex polytope to summarize multivariate data. For fixed $k$, the method finds a convex polytope with $k$ vertices, called archetype points, such that the polytope is contained in the convex hull of the data and the mean squared distance between the data and the polytope is minimal. In
Braxton Osting +3 more
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Unravelling the instability of mutational signatures extraction via archetypal analysis
Frontiers in Genetics, 2023 The high cosine similarity between some single-base substitution mutational signatures and their characteristic flat profiles could suggest the presence of overfitting and mathematical artefacts.
Corrado Pancotti +5 more
doaj +1 more source
Combining electro- and magnetoencephalography data using directional archetypal analysis
Frontiers in Neuroscience, 2022 Metastable microstates in electro- and magnetoencephalographic (EEG and MEG) measurements are usually determined using modified k-means accounting for polarity invariant states.
Anders S. Olsen +6 more
doaj +1 more source
Near-Convex Archetypal Analysis [PDF]
IEEE Signal Processing Letters, 2020 Nonnegative matrix factorization (NMF) is a widely used linear dimensionality reduction technique for nonnegative data. NMF requires that each data point is approximated by a convex combination of basis elements. Archetypal analysis (AA), also referred to as convex NMF, is a well-known NMF variant imposing that the basis elements are themselves convex ...
Pierre De Handschutter +3 more
openaire +4 more sources