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Demand is mounting in the industry for scalable GPU-based deep learning systems. Unfortunately, existing training applications built atop popular deep learning frameworks, including Caffe, Theano, and Torch, etc, are incapable of conducting distributed GPU training over large-scale clusters.To remedy such a situation, this paper presents Nexus, a platform that allows existing deep learning frameworks...
This paper proposes a deep learning architecture based on Residual Network that dynamically adjusts the number of executed layers for the regions of the image. This architecture is end-to-end trainable, deterministic and problem-agnostic. It is therefore applicable without any modifications to a wide range of computer vision problems such as image classification, object detection and image segmentation...
Feature location is the activity of identifying an initial location in the source code that implements special functionality in a software system. Existing techniques for feature location broadly fall into three categories, based on the type of information they use: text, static, and dynamic. The techniques based on dynamic may generate large amount of data and is difficult to utilize. This paper...
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