Results 1 to 10 of about 3,100,522 (340)
A reappraisal of the Friedman-Kaldor debate in the light of the great recession [PDF]
SocioEconomic Challenges, 2022 This paper summarizes the arguments and counterarguments within the scientific discussion on the issue of the exogenous and endogenous money supply theories, developed by Milton Friedman and Nicholas Kaldor in the 1960s-1970s.
Alexandre Reichart
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Development of Attention and Accuracy in Learning a Categorization Task
Frontiers in Psychology, 2021 Being able to categorize objects as similar or different is an essential skill. An important aspect of learning to categorize is learning to attend to relevant features (i.e., features that determine category membership) and ignore irrelevant features of
Leonora C. Coppens +6 more
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Deep Contextualized Word Representations [PDF]
North American Chapter of the Association for Computational Linguistics, 2018 We introduce a new type of deep contextualized word representation that models both (1) complex characteristics of word use (e.g., syntax and semantics), and (2) how these uses vary across linguistic contexts (i.e., to model polysemy).
Matthew E. Peters +6 more
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DeepWalk: online learning of social representations [PDF]
Knowledge Discovery and Data Mining, 2014 We present DeepWalk, a novel approach for learning latent representations of vertices in a network. These latent representations encode social relations in a continuous vector space, which is easily exploited by statistical models.
Bryan Perozzi, Rami Al-Rfou, S. Skiena
semanticscholar +1 more source
LXMERT: Learning Cross-Modality Encoder Representations from Transformers [PDF]
Conference on Empirical Methods in Natural Language Processing, 2019 Vision-and-language reasoning requires an understanding of visual concepts, language semantics, and, most importantly, the alignment and relationships between these two modalities.
Hao Hao Tan, Mohit Bansal
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Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation [PDF]
Conference on Empirical Methods in Natural Language Processing, 2014 In this paper, we propose a novel neural network model called RNN Encoder‐ Decoder that consists of two recurrent neural networks (RNN). One RNN encodes a sequence of symbols into a fixedlength vector representation, and the other decodes the ...
Kyunghyun Cho +6 more
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Frontiers in Psychology, 2020 Learners face various obstacles during learning from illustrated texts that can be conceptualized against the backdrop of frameworks of self-regulated learning.
Emely Hoch +4 more
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VinVL: Revisiting Visual Representations in Vision-Language Models
Computer Vision and Pattern Recognition, 2021 This paper presents a detailed study of improving visual representations for vision language (VL) tasks and develops an improved object detection model to provide object-centric representations of images.
Pengchuan Zhang +7 more
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Self-Attention with Relative Position Representations [PDF]
North American Chapter of the Association for Computational Linguistics, 2018 Relying entirely on an attention mechanism, the Transformer introduced by Vaswani et al. (2017) achieves state-of-the-art results for machine translation.
Peter Shaw +2 more
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