منابع مشابه
Feedforward Neural Networks
Here x is an input, y is a “label”, v ∈ Rd is a parameter vector, and f(x, y) ∈ Rd is a feature vector that corresponds to a representation of the pair (x, y). Log-linear models have the advantage that the feature vector f(x, y) can include essentially any features of the pair (x, y). However, these features are generally designed by hand, and in practice this is a limitation. It can be laborio...
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For many practical problem domains the use of neural networks has led to very satisfactory results. Nevertheless the choice of an appropriate, problem specific network architecture still remains a very poorly understood task. Given an actual problem, one can choose a few different architectures, train the chosen architectures a few times and finally select the architecturewith the best behaviou...
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We present flattened convolutional neural networks that are designed for fast feedforward execution. The redundancy of the parameters, especially weights of the convolutional filters in convolutional neural networks has been extensively studied and different heuristics have been proposed to construct a low rank basis of the filters after training. In this work, we train flattened networks that ...
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ژورنال
عنوان ژورنال: ACM SIGMETRICS Performance Evaluation Review
سال: 2019
ISSN: 0163-5999
DOI: 10.1145/3308897.3308958