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Class (philosophy)

About: Class (philosophy) is a research topic. Over the lifetime, 821 publications have been published within this topic receiving 28000 citations.


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Journal ArticleDOI
TL;DR: In this paper , a new 3-way decision theory was proposed for solving multi-criteria decision-making (MCDM) problems and applied it to realistic MCDM problems.

15 citations

Journal ArticleDOI
TL;DR: In this paper, the authors argue that a stochastic dominance interpretation can be maintained only at the price of either an arbitrary choice of specification which undermines its intuitive force or, alternatively, of an unintended restriction of the class of characterized preferences.
Abstract: IN AN INTERESTING RECENT PAPER, Sarin and Wakker (1992) (henceforth S-W) have provided a new axiomatization of expected utility maximization with "capacities" (CEU). Its simplicity is attractive in that it provides a constructive interpretation of the role of capacities and Choquet integration in the main representation theorem. An important issue raised by the paper is the interpretation of the key Axiom P4 ("Cumulative Dominance"). S-W suggest an appreciation of the axiom as an adaptation of stochastic dominance principles to nonadditive-probability contexts, most eloquently on page 1260. If viable, such an interpretation would supply the CEU model with a powerful intuitive foundation that has been lacking so far. This note argues that a stochastic dominance interpretation can be maintained only at the price of either an arbitrary choice of specification which undermines its intuitive force or, alternatively, of an unintended restriction of the class of characterized preferences. Two logically independent arguments are presented. The first points out an arbitrariness in the definition of the more-likely-than relation in terms of preferences (Proposition 1). The second shows a similar arbitrariness in the definition of a "stochastic dominance" relation in terms of a more-likely-than relation (Proposition 2). In each case, the invoked symmetry conditions yield a characterization of CEU preferences with symmetric capacities, a nontrivial generalization of the SEU model that has received little attention in the literature. For notation and definitions, the reader is referred to S-W's paper. S-W's concern is to develop an intuitively convincing axiomatization of CEU-representable preference relations. Their key Axiom P4 is formulated in terms of a more-likelythan relation > on the algebra v of events that is defined in terms of the preference relation a on the set of acts Y To facilitate the subsequent discussion, their "definition" is introduced here formally as a "condition" on the pair of relations (a, >):

15 citations

Posted Content
TL;DR: In this paper, the authors show that renormalized oscillation results can be obtained in a natural way through consideration of the Maslov index associated with appropriately chosen paths of Lagrangian subspaces.
Abstract: Working with a general class of linear Hamiltonian systems on $[0, 1]$, we show that renormalized oscillation results can be obtained in a natural way through consideration of the Maslov index associated with appropriately chosen paths of Lagrangian subspaces of $\mathbb{C}^{2n}$. We verify that our applicability class includes Dirac and Sturm-Liouville systems, as well as a system arising from differential-algebraic equations for which the spectral parameter appears nonlinearly.

15 citations

Journal ArticleDOI
06 May 2022-Axioms
TL;DR: The results show that interval-valued pseudo overlap functions can not only be used to obtain the same rankings, but also be more flexible, simple and widely used.
Abstract: A class of interval-valued OWA operators can be constructed from interval-valued overlap functions with interval-valued weights, which plays an important role in solving multi-attribute decision making (MADM) problems considering interval numbers as attribute values. Among them, when the importance of multiple attributes is different, it can only be calculated by changing the interval-valued weights. In fact, we can directly abandon the commutativity and extend the interval-valued overlap functions (IO) to interval-valued pseudo overlap functions (IPO) so that function itself implies the weights of the attributes, thus there is no need to calculate the OWA operator, which is more flexible in applications. In addition, the similar generalization on interval-valued pseudo t-norms obtained from interval-valued t-norms further enhances the feasibility of our study. In this paper, we mainly present the notion of interval-valued pseudo overlap functions and a few their qualities, including migrativity and homogeneity, and give some construction theorems and specific examples. Then, we propose the definitions of residuated implications induced by interval-valued pseudo overlap functions, give their equivalent forms, and prove some properties satisfied by them. Finally, two application examples about IPO to interval-valued multi-attribute decision making (I-MADM) are described. The results show that interval-valued pseudo overlap functions can not only be used to obtain the same rankings, but also be more flexible, simple and widely used.

15 citations

Journal ArticleDOI
TL;DR: Zhang et al. as discussed by the authors proposed an improved ViT architecture, which adds a shared MLP head to the output of each patch token to balance the feature learning on the class and patch tokens.
Abstract: Recently, the Vision Transformer (ViT) model has been used for various computer vision tasks, due to its advantages to extracting long-range features. To better integrate the long-range features useful for classification, the standard ViT adds a class token, in addition to patch tokens. Despite state-of-the-art results on some traditional vision tasks, the ViT model typically requires large datasets for supervised training, and thus, it still face challenges in areas where it is difficult to build large datasets, such as medical image analysis. In the ViT model, only the output corresponding to the class token is fed to a Multi-Layer Perceptron (MLP) head for classification, and the outputs corresponding to the patch tokens are exposed. In this paper, we propose an improved ViT architecture (called ViT-Patch), which adds a shared MLP head to the output of each patch token to balance the feature learning on the class and patch tokens. In addition to the primary task, which uses the output of the class token to discriminate whether the image is malignant, a secondary task is introduced, which uses the output of each patch token to determine whether the patch overlaps with the tumor area. More interestingly, due to the correlation between the primary and secondary tasks, the supervisory information added to the patch tokens help with improving the performance of the primary task on the class token. The introduction of secondary supervision information also improves the attention interaction among the class and patch tokens. And by this way, ViT reduces the demand on dataset size. The proposed ViT-Patch is validated on a publicly available dataset, and the experimental results show its effectiveness for both malignant identification and tumor localization.

15 citations


Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20241
202311,771
202223,753
2021380
2020186
201962