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Computer Science > Computer Vision and Pattern Recognition
Title: Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
Abstract: Rectified activation units (rectifiers) are essential for state-of-the-art neural networks. In this work, we study rectifier neural networks for image classification from two aspects. First, we propose a Parametric Rectified Linear Unit (PReLU) that generalizes the traditional rectified unit. PReLU improves model fitting with nearly zero extra computational cost and little overfitting risk. Second, we derive a robust initialization method that particularly considers the rectifier nonlinearities. This method enables us to train extremely deep rectified models directly from scratch and to investigate deeper or wider network architectures. Based on our PReLU networks (PReLU-nets), we achieve 4.94% top-5 test error on the ImageNet 2012 classification dataset. This is a 26% relative improvement over the ILSVRC 2014 winner (GoogLeNet, 6.66%). To our knowledge, our result is the first to surpass human-level performance (5.1%, 超越K線戰法和斐波那契技術 Russakovsky et al.) on this visual recognition challenge.
吞噬星空:超越战神究竟是什么境界,达到此境界又有什么特殊技能
导读:在吞噬星空中,人类若想拥有对抗怪兽的实力,就必须成为“武者”,而想成为武者,也并不是心里想就行了,不仅需要自己有天赋,而且还需要自身的努力,而在武者的境界当中,分为战士、战将、战神、而每一个境界又分为低中高三小级,每一位成为战神的强者,在国家都拥有着极高的地位,一位战神所展现的实力,可是有着轻易毁灭一座大厦,而在地球篇中,战神之上还有这超越战神,那么,超越战神究竟是什么境界,达到此境界,又有什么特殊技能?
超越战神只是人们在地球上的称呼而已,而在整个宇宙当中,超越战神被称为行星级,达到行星级的强者,只是宇宙中修炼的开始而已,不过,在地球当中,却是人类巅峰的存在,因为地球资源有限,再加上对于宇宙的认知比较少,所以整个地球当中,能达到超越战神境界的强者,也只有50多位而已,而在众多超越战神的强者当中,当属极限武馆的“洪”排在第一,他也被其成为地球第一强者。
而极限武馆也是超越战神最多的势力之一,在“洪”的手下,三大亲位以及五大巡察使,再加上即将崛起的罗峰,“洪”的身边一共有九位超越战神的强者,而超越战神不仅仅是实力上的提升,他还会拥有一个元素的技能,比如,光线寒冰火焰之类,比如当初HR联盟的第三仪长,拥有冰雪大帝之称的默汉德森,因为当初与罗峰在木伢晶的争夺上面,起了争执,与罗峰大打出手。
要知道,这默汉德森乃是美利坚的第一强者,身为第三仪长的他,也是这世间仅次于“洪”与雷神的存在,而且他这一手的冰雪之力更是控制的炉火纯青,不过,让这默汉德森也没想到的是,罗峰凭借着盾天梭,竟然打的他节节败退,最终连他也奈何不了罗峰,要知道,这莫汉德森凭借着行星级的实力,有了如今的地位,在加上存活了这么久,如今却被一个20岁的毛头小子给教训了,心里自然是不爽。
除了没汉德森之外,当初与罗峰结仇的李耀,再之后,即将被问斩之时,突破极限的他也达到了行星级,当时李要拥有的技能便是光线,李耀本以为自己达到了突破战神的境界,便拥有了斩杀罗峰的实力,就连当时的洪雨雷神也觉得罗峰可能会有麻烦,决定出手帮忙,不过,让他们万万没想到的是,他们派出去的人带回来的消息便是,李耀已经被罗峰给斩杀,这也让“洪”也对罗峰愈发的看重,那么各位朋友们知道罗峰达到超越战神之后,会获得哪个特殊技能吗。
好了,以上关于《吞噬星空》的内容,仅仅是个人观点,不喜勿喷。
若有疑问的小伙伴,可以在下方评论中,评论出你们的观点哦!看完之后,别忘了给枯海点个关注哦,后续还有更多精彩作品!
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Computer Science > Machine Learning
Title: Lookahead Optimizer: k steps forward, 1 step back
Abstract: The vast majority of successful deep neural networks are trained using variants of stochastic gradient descent (SGD) algorithms. Recent attempts to improve SGD can be broadly categorized into two approaches: (1) adaptive learning rate schemes, such as AdaGrad and Adam, and (2) accelerated schemes, such as heavy-ball and Nesterov momentum. In this paper, we propose a new optimization algorithm, Lookahead, that is orthogonal to these previous approaches and iteratively updates two sets of weights. Intuitively, the algorithm chooses a search direction by \emph at the sequence of "fast weights" generated by another optimizer. We show that Lookahead improves the learning stability and lowers the variance of its inner optimizer with negligible computation and memory cost. We empirically demonstrate Lookahead can significantly improve the performance of SGD and Adam, even with their default hyperparameter settings on ImageNet, CIFAR-10/100, neural machine translation, and Penn Treebank.
Comments: | 8 pages |
Subjects: | Machine Learning (cs.LG) ; Neural and Evolutionary Computing (cs.NE); Machine Learning (stat.ML) |
Cite as: | arXiv:1907.08610 [cs.LG] |
(or arXiv:1907.08610v1 [cs.LG] for this version) | |
https://doi.org/10.48550/arXiv.1907.08610 超越K線戰法和斐波那契技術 |
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Submission history
From: 超越K線戰法和斐波那契技術 Michael Zhang [view email]
[v1] Fri, 19 Jul 2019 17:59:50 UTC (3,005 KB)
[v2] Tue, 3 Dec 2019 15:55:38 UTC (2,877 KB)