Academic literature on the topic 'Degrees'

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Journal articles on the topic "Degrees"

1

Soskova, A. A., and I. N. Soskov. "Quasi-minimal degrees for degree spectra." Journal of Logic and Computation 23, no. 6 (2013): 1319–34. http://dx.doi.org/10.1093/logcom/ext045.

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2

Gobeski, Adam, and Marcin Morzycki. "Percentages, Relational Degrees, and Degree Constructions." Semantics and Linguistic Theory 27 (August 3, 2018): 721. http://dx.doi.org/10.3765/salt.v27i0.4142.

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Comparatives and equatives are usually assumed to differ only in that comparatives require that one degree be greater than another, while equatives require that it be at least as great. Unexpectedly, though, the interpretation of percentage measure phrases differs fundamentally between the constructions. This curious asymmetry is, we suggest, revealing. It demonstrates that comparatives and equatives are not as similar as one might have thought. We propose an analysis of these facts in which the interpretation of percentage phrases follows straightforwardly from standard assumptions enriched with two additional ones: that percentage phrases denote ‘relational degrees’ (type <d,d>) and that the equative morpheme is uninterpreted.
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3

Huppert, Bertram, and Olaf Manz. "Degree-problems I squarefree character degrees." Archiv der Mathematik 45, no. 2 (1985): 125–32. http://dx.doi.org/10.1007/bf01270483.

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4

Manz, Olaf. "Degree problems II π - separable character degrees". Communications in Algebra 13, № 11 (1985): 2421–31. http://dx.doi.org/10.1080/00927878508823281.

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5

Pardey, Johannes, and Dieter Rautenbach. "Vertex degrees close to the average degree." Discrete Mathematics 346, no. 12 (2023): 113599. http://dx.doi.org/10.1016/j.disc.2023.113599.

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6

Chong, C. T., and R. G. Downey. "Degrees bounding minimal degrees." Mathematical Proceedings of the Cambridge Philosophical Society 105, no. 2 (1989): 211–22. http://dx.doi.org/10.1017/s0305004100067694.

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A set is called n-generic if it is Cohen generic for n-quantifier arithmetic. A (Turing) degree is n-generic if it contains an n-generic set. Our interest in this paper is the relationship between n-generic (indeed 1-generic) degrees and minimal degrees, i.e. degrees which are non-recursive and which bound no degrees intermediate between them and the recursive degree. It is known that n-generic degrees and minimal degrees have a complex relationship since Cohen forcing and Sacks forcing are mutually incompatible. The goal of this paper is to show.
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7

van der Hofstad, Remco, and Nelly Litvak. "Degree-Degree Dependencies in Random Graphs with Heavy-Tailed Degrees." Internet Mathematics 10, no. 3-4 (2014): 287–334. http://dx.doi.org/10.1080/15427951.2013.850455.

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8

van der Hoorn, Pim, and Nelly Litvak. "Degree-Degree Dependencies in Directed Networks with Heavy-Tailed Degrees." Internet Mathematics 11, no. 2 (2014): 155–79. http://dx.doi.org/10.1080/15427951.2014.927038.

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9

Song, Joshua. "Degrees of Confidence as a Legal Tool to Assess AI System Liability." Michigan Technology Law Review, no. 29.1 (2022): 111. http://dx.doi.org/10.36645/mtlr.29.1.degrees.

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AI systems have become increasingly integrated into our everyday lives, and harms caused by these systems have graduated from raising hypothetical ethical concerns to questions of actual legal liability. Civil liability schemes are generally designed to address harms caused by humans; thus, it may be tempting to analogize new types of harms caused by AI systems to familiar harms caused by humans in order to justify commandeering existing human-centered legal tools to assess AI liability. However, the analogy is inappropriate and misrepresents salient legal differences in how harms are committed by humans and AI systems. Thus, “as is often the case when analogical reasoning cannot justifiably stretch extant law to address novel legal questions raised by a new technology, new law is needed.” First, I will discuss the legally salient difference between human and AI decision-making. Second, I will highlight two specific AI harms – autonomous vehicle product liability harms and predictive privacy harms – for which the analogy of human liability is insufficient. Finally, I will propose a new legal tool that may supplement the deficiencies in applying human liability schemes to AI harms.
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10

Arslanov, Marat M., Iskander Sh Kalimullin, and Steffen Lempp. "On Downey's conjecture." Journal of Symbolic Logic 75, no. 2 (2010): 401–41. http://dx.doi.org/10.2178/jsl/1268917488.

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AbstractWe prove that the degree structures of the d.c.e. and the 3-c.e. Turing degrees are not elementarily equivalent, thus refuting a conjecture of Downey. More specifically, we show that the following statement fails in the former but holds in the latter structure: There are degreesf>e>d>0such that any degreeu≤fis either comparable with botheandd, or incomparable with both.
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