A heretical tale about heresy or when words do matter
نویسندگان
چکیده
منابع مشابه
When do Numbers Really Matter?
Common wisdom has it that small distinctions in the probabilities quantifying a belief network do not matter much for the results of probabilistic queries. Yet, one can develop realistic scenarios under which small variations in network probabilities can lead to significant changes in computed queries. A pending theoretical question is then to analytically characterize parameter changes that do...
متن کاملThink about Neurobrucellosis, When a Man Cries
Neurobrucellosis (N.B) is a rare and severe form of systemic Brucella infection. We introduced an unusual case that “Psychologic Symptoms” was the most prominent complaints of his family. He was a 50-year-old man who has worked in butchery. His problems had begun 2 months prior to his admission with mood disorders, arthralgia, weakness, headache, and night sweats; he has recurrent crying with n...
متن کاملWhen Do Words Promote Analogical Transfer?
The purpose of this paper is to explore how and when verbal labels facilitate relational reasoning and transfer. We review the research and theory behind two ways words might direct attention to relational information: (1) words generically invite people to compare and thus highlight relations (the Generic Tokens [GT] hypothesis), and/or (2) words carry semantic cues to common structure (the Cu...
متن کاملWhen Do Match-Compilation Heuristics Matter?
Modern, statically typed, functional languages define functions by pattern matching. Although pattern matching is defined in terms of sequential checking of a value against one pattern after another, real implementations translate patterns into automata that can test a value against many patterns at once. Decision trees are popular automata. The cost of using a decision tree is related to its s...
متن کاملMulti-Domain Learning: When Do Domains Matter?
We present a systematic analysis of existing multi-domain learning approaches with respect to two questions. First, many multidomain learning algorithms resemble ensemble learning algorithms. (1) Are multi-domain learning improvements the result of ensemble learning effects? Second, these algorithms are traditionally evaluated in a balanced class label setting, although in practice many multido...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: HTS Teologiese Studies / Theological Studies
سال: 2019
ISSN: 2072-8050,0259-9422
DOI: 10.4102/hts.v75i3.5023