highway

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Highway Networks

There is plenty of theoretical and empirical evidence that depth of neural networks is a crucial ingredient for their success. However, network training becomes more difficult with increasing depth and training of very deep networks remains an open problem. In this extended abstract, we introduce a new architecture designed to ease gradient-based training of very deep networks. We refer to netw...

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Highway-LSTM and Recurrent Highway Networks for Speech Recognition

Recently, very deep networks, with as many as hundreds of layers, have shown great success in image classification tasks. One key component that has enabled such deep models is the use of “skip connections”, including either residual or highway connections, to alleviate the vanishing and exploding gradient problems. While these connections have been explored for speech, they have mainly been ex...

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Driving on the Highway Driving on the Highway

| This paper deals with a particular kinodynamic 4] trajectory planning problem that we call thèhighway problem'. It consists in planning a time-optimal trajectory for a vehicle which is travelling in a structured workspace amidst other vehicles and is subject to constraints on its velocity and acceleration. By structured workspace, we mean that there exists lanes within which the vehicles are ...

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ژورنال

عنوان ژورنال: Tessera

سال: 2002

ISSN: 1923-9408,0840-4631

DOI: 10.25071/1923-9408.25291