人工智能下载,深度学习下载列表第517页

[深度学习] Reversible Recurrent Neural Networks.pdf

说明：Recurrent neural networks (RNNs) provide state-of-the-art performance in processing sequential data but are memory intensive to train, limiting the flexibility of RNN models which can be trained. Reversible RNNs—RNNs for which the hidden-to-hidden
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[深度学习] Streaming Graph Neural Networks.pdf

说明：Graphs are essential representations of many real-world data such as social networks. Recent years have witnessed the increasing efforts made to extend the neural network models to graph-structured data. These methods, which are usually known as th
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[深度学习] Generalization in Deep Learning.pdf

说明：With a direct analysis of neural networks, this paper presents a mathematically tight generalization theory to partially address an open problem regarding the generalization of deep learning. Unlike previous bound-based theory, our main theory is q
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[深度学习] Generalization in Machine Learning via Analytical Learning Theory.pdf

说明：This paper introduces a novel measure-theoreticlearning theory to analyze generalization behaviors of practical interest. The proposed learningtheory has the following abilities: 1) to utilizethe qualities of each learned representation onthe path fr
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[深度学习] Learning representations on graphs.pdf

说明：Networks are everywhere. Popular examples include social networks, the hyperlinked World Wide Web, transportation networks, electricity power networks and biological gene networks. Networks are typically represented as a graph whose vertices repr
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[深度学习] Model-driven deep-learning.pdf

说明：With the arrival of the big data era, data requirements are gradually no longer an obstacle (at least for many areas), but the determination of network topology is still a bottleneck. This is mainly due to the lack of theoretical understandings
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[深度学习] 639-Multi-scale Orderless Pooling of Deep Convolutional Activation Features.pdf

说明：Deep convolutional neural networks (CNN) have shown their promise as a universal representation for recognition. However, global CNN activations lack geometric invariance, which limits their robustness for classification and matching of highly var
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[深度学习] 771-A Survey on Concept Drift Adaptation.pdf

说明：Concept drift primarily refers to an online supervised learning scenario when the relation between the input data and the target variable changes over time. Assuming a general knowledge of supervised learning in this paper we characterize adaptive l
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[深度学习] 936-A Review on Multi-Label Learning Algorithms.pdf

说明：Multi-label learning studies the problem where each example is represented by a single instance while associated with a set of labels simultaneously. During the past decade, significant amount of progresses have been made toward this emerging machi
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