نتایج جستجو برای: contrastive and tempral

تعداد نتایج: 16827575  

Journal: :Journal of memory and language 2010
Scott H Fraundorf Duane G Watson Aaron S Benjamin

The effects of pitch accenting on memory were investigated in three experiments. Participants listened to short recorded discourses that contained contrast sets with two items (e.g. British scientists and French scientists); a continuation specified one item from the set. Pitch accenting on the critical word in the continuation was manipulated between non-contrastive (H* in the ToBI system) and...

Journal: :Semantics and Pragmatics 2012

Journal: :Theoria 2021

In this paper, I outline an account of the structure perceptual justification that develops Wittgenstein's thought possibility acquiring any degree for our beliefs depends on placing certain propositions outside route empirical inquiry, turning them into “hinges” rational evaluations. The proposal is akin to “moderate” accounts justification; however, it conjoins insight with explanationist and...

2015
Noah Constant Elisabeth Selkirk

CONTRASTIVE TOPIC: MEANINGS AND REALIZATIONS

1991
Diana Santos

Foreword This report originated in a paper I was to write with Lauri Carlson on the semantics of tense and aspect, and which never became ready, since the formalization part could not be made good enough in the required schedule ((rst trimester of 1991). In the original paper, I tried to describe the data and propose a theory of my own. Now I decided to select only the description of the proble...

Journal: :Lecture Notes in Computer Science 2023

The development of unsupervised hashing is advanced by the recent popular contrastive learning paradigm. However, previous learning-based works have been hampered (1) insufficient data similarity mining based on global-only image representations, and (2) hash code semantic loss caused augmentation. In this paper, we propose a novel method, namely Weighted Contrative Hashing (WCH), to take step ...

Journal: :Cahiers de praxématique 2002

Journal: :Lecture Notes in Computer Science 2022

AbstractThe success of deep learning is usually accompanied by the growth in neural network depth. However, traditional training method only supervises at its last layer and propagates supervision layer-by-layer, which leads to hardship optimizing intermediate layers. Recently, has been proposed add auxiliary classifiers layers networks. By these with supervised task loss, can be applied shallo...

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