Knowledge-fallibilism is a species of genus that I call knowledge-failabilism. Each theory knowledge's nature. One apparent challenge to knowledge-failabilism's truth the prima facie absurdity Moorean assertions like ‘It's raining but do not believe it is.’ Does each such assertion convey an implicit and unfortunate contrast, even contradiction? argue this Untenable Contrast analysis fails: no ...

Este artículo analiza la adaptación cinematográfica de novela 59 Degrees and Raining: The Story of Perdita Durango Álex Iglesia, contextualizando literatura Barry Gifford, su imaginario cinematográfico, relación con industria y otros directores. Se consideran los referentes sobre que se sistematiza el argumento del libro adaptación, así como nexos, influencias omisiones en fundamenta trasvase. ...

The construction [X, you are/were Y], where X is a spatio-temporal addressee, widely attested on Dutch social media. We investigated this in Twitter corpus, and found that users use the to tell their audience about current or recent experience at location addressed, while same time evaluating said experience. Reference first-hand not overtly expressed, yet it an essential interpretive aspect of...

If we think, as Ramsey did, that a degree of belief that P is a stronger or weaker tendency to act as if P , then it is clear that not only uncertainty, but also vagueness, gives rise to degrees of belief. If I like hot coffee and do not know whether the coffee is hot or cold, I will have some tendency to reach for a cup; if I like hot coffee and know that the coffee is borderline hot, I will h...

Backpropagation (or backprop) algorithm is one of the well-known algorithms in neural networks. It is capable to deal with various types of data and also able to model a complex decision system. Some problem domains involve a large amount of data. The bigger the number of input or hidden units is, the more complex the model would be. Hence, reducing the network complexity would be an advantage ...

Support V ectorMachines (SVMs) ha vebecome an increasingly popular tool for machine learning tasks involving classi cation, regression or no velty detection. They exhibit good generalisation performance on many reallife datasets and the approach is well-motivated theoretically. T raining involv es optimisation of a convex cost function, there are relatively few free parameters to adjust and the...