Broiler Address第四季依然由Reece Shearsmith和Steve Pemberton两位怪才主演，依然是6集。何永强接过酒杯，放在眼前端详片刻：从前，这种杯子，我连看一眼都不屑。在博翰大学的校园里聚集着这样一众好友，他们是热爱打听各路消息的花心小子华又希、傲娇又仗义的酒店大亨独女吴安珀、外号“康公子”的帅气女生康薇薇、毕业三年仍是学校偶像的应冬，艺术系校花万嘉、校园甜心梅宝，靠谱老实的经济男韩定一。在距离大学毕业还剩短短几个月的时间里，他们一起享受着最后的校园时光，也一起遭遇和见证着一系列的爱情故事……由余文乐饰演的铁板烧厨师华三毛为了寻找消失的初恋女友来到他们身边，用执着和痴情打动了每一个人；谭维维饰演的偶像歌手艾迪带着多年的心结来为初恋圆梦，重温校园恋情的简单美好；老谋深算的欺诈高手高琦（陈法蓉饰）用爱情牟利却亲情失算；事业有成的娱乐记者叶飞飞（周笔畅饰）本欲揭穿惊天八卦却最让自己陷入两难；脾气古怪的餐饮界巨子欧辉（金汎饰）上演了一段刻骨铭心的爱情；超人气影视红星洛依（杨幂饰）与旧爱重逢却未能将爱情进行到底……目睹着一段又一段或感动或遗憾的情感故事，几个好朋友之间也对自己的爱情和友情做出了选择……Opponents continue to use new inputs/payloads to detect classifiers in an attempt to evade detection. Such payloads are called antagonistic inputs because they are explicitly designed to bypass the classifier.For codes of the same length, theoretically, the further the coding distance between any two categories, the stronger the error correction capability. Therefore, when the code length is small, the theoretical optimal code can be calculated according to this principle. However, it is difficult to effectively determine the optimal code when the code length is slightly larger. In fact, this is an NP-hard problem. However, we usually do not need to obtain theoretical optimal codes, because non-optimal codes can often produce good enough classifiers in practice. On the other hand, it is not that the better the theoretical properties of coding, the better the classification performance, because the machine learning problem involves many factors, such as dismantling multiple classes into two "class subsets", and the difficulty of distinguishing the two class subsets formed by different dismantling methods is often different, that is, the difficulty of the two classification problems caused by them is different. Therefore, one theory has a good quality of error correction, but it leads to a difficult coding for the two-classification problem, which is worse than the other theory, but it leads to a simpler coding for the two-classification problem, and it is hard to say which is better or weaker in the final performance of the model.
