Related papers: Piecewise Linear Activation Functions For More Eff…
This paper has been withdrawn due to upload of another version of it as a new preprint: gr-qc/0404097
This paper has been withdrawn by the corresponding author because the newest version is now published in Journal of Discrete Algorithms.
This paper has been withdrawn by the authors; its contents are superseded by that of hep-th/0105305 and hep-th/0212275.
This paper has been withdrawn by the first author due to incomplete bibliography and incorporation of multiple formats in the same file.
This article has been withdrawn by arXiv administrators because it plagiarises http://www2.ece.ohio-state.edu/~ekici/papers/crnroutingsurvey.pdf
This paper had been withdrawn because the prime reported effect had not been confirmed in further investigations (see arXiv:0812.4488 [hep-lat]).
This paper has been withdrawn.
Relu Fully Connected Networks are ubiquitous but uninterpretable because they fit piecewise linear functions emerging from multi-layered structures and complex interactions of model weights. This paper takes a novel approach to piecewise…
This article has been withdrawn by arXiv administrators due to excessive unattributed and verbatim text overlap with the pre-existing Wikipedia article on redshift
Admin note: withdrawn by arxiv admin due to use of pseudonym against arXiv policy.
This paper has been withdrawn by the author because the conclusions reached in it are incorrect.
This paper had been withdrawn because the prime reported effect had not been confirmed in further investigations (see arXiv:0812.4488 [hep-lat]).
This submission has been withdrawn by arXiv admins because it contains inappropriate overlap with arXiv:physics/0603087.
In recent years, Deep Reinforcement Learning (DRL) algorithms have achieved state-of-the-art performance in many challenging strategy games. Because these games have complicated rules, an action sampled from the full discrete action…
This paper has been withdrawn by the authors due to an incorrect analysis.
This submission has been withdrawn by the authors because it is a duplicate of arXiv:hep-ph/0611336. It was due to a technical submission error by the authors.
This article has been withdrawn.
This paper has been withdrawn by the authors, due a oversimplified decoherence model. It will be substituted by a new work.
Understanding the loss surface of a neural network is fundamentally important to the understanding of deep learning. This paper presents how piecewise linear activation functions substantially shape the loss surfaces of neural networks. We…
This paper has been withdrawn by the author, because a better treatment is given in the author's Phd. thesis (Sections 3.4.6 and 4.4), now available on the arxiv.