Computational infrastructure for developing deep machine learning models

用于开发深度机器学习模型的计算基础设施

• 批准号: LE160100090
• 负责人: Prof Ian Reid
• 金额: $ 16.67万
• 依托单位: The University of Adelaide
• 依托单位国家: 澳大利亚
• 项目类别: Linkage Infrastructure, Equipment and Facilities
• 财政年份: 2016
• 资助国家: 澳大利亚
• 起止时间: 2016-04-11 至 2017-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LE160100090
• 关键词: Computational; infrastructure; developing; deep; machine

Computational infrastructure for developing deep machine learning models: The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object recognition in images, speech recognition and automatic translation, bringing the prospect of machine intelligence closer than ever. Modern machine learning techniques have had huge impact in the last decade in fields such as robotics, computer vision and data analytics. The facility would enable Australian researchers to develop, learn and apply deep networks to problems of national importance in robotic vision and big data analytics.

用于开发深度机器学习模型的计算基础设施： 用于开发深度机器学习模型的计算基础设施旨在通过提供训练和评估网络所需的专业计算来实现深度神经网络模型的机器学习的新发展。在过去的三年里，深度网络已经打破了图像中的对象识别、语音识别和自动翻译等任务的性能上限，使机器智能的前景比以往任何时候都更加接近。现代机器学习技术在过去十年中对机器人、计算机视觉和数据分析等领域产生了巨大影响。该设施将使澳大利亚研究人员能够开发，学习和应用深度网络解决机器人视觉和大数据分析中的国家重要问题。