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算法预测结构化数据
Algorithms for Predicting Structured Data |
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| 课程网址: |
http://videolectures.net/ecmlpkdd2010_gartner_vembu_apsd/
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| 主讲教师: |
Thomas Gartner, Shankar Vembu
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| 开课单位: |
弗劳恩霍夫协会
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| 开课时间: |
2010-11-16
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| 课程语种: |
英语
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| 中文简介: |
结构化预测是预测内部结构复杂的多个输出及其之间的依赖关系的问题。用于预测结构化数据的算法和模型已经使用了很长时间。例如, 递归神经网络和隐藏马尔可夫模型在语音识别等时间模式识别问题中发现了有趣的应用。随着上世纪 9 0年代支持向量机的引入, 机器学习界对判别学习模型产生了极大的兴趣。在本教程中, 我们计划介绍用于预测结构化数据的判别学习算法的最新发展。我们相信本教程将是机器学习研究人员的兴趣, 包括研究生, 他们希望获得结构化预测和最先进的方法来解决这个问题的理解。结构化预测在自然语言处理、计算机视觉和计算生物学等领域有几个应用, 仅举几例。我们相信, 在上述应用领域工作的研究人员也会对本教程中介绍的材料感兴趣。
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| 课程简介: |
Structured prediction is the problem of predicting multiple outputs with complex internal structure and dependencies among them. Algorithms and models for predicting structured data have been in use for a long time. For example, recurrent neural networks and hidden Markov models have found interesting applications in temporal pattern recognition problems such as speech recognition. With the introduction of support vector machines in the 1990s, there has been a lot of interest in the machine learning community in discriminative models of learning. In this tutorial, we plan to cover recent developments in discriminative learning algorithms for predicting structured data. We believe this tutorial will be of interest to machine learning researchers including graduate students who would like to gain an understanding of structured prediction and state-of-the-art approaches to solve this problem. Structured prediction has several applications in the areas of natural language processing, computer vision and computational biology, just to name a few. We believe the material presented in this tutorial will also be of interest to researchers working in the aforementioned application areas.
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| 关 键 词: |
计算机科学; 机器学习; 结构化数据
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| 课程来源: |
视频讲座网
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| 最后编审: |
2020-06-11：dingaq
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| 阅读次数: |
61
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