开课单位--KDD 2016研讨会

1
Deep‐Learning: Investigating feed‐forward Deep Neural Networks hyper‐parameters and Comparison of Performance to Shallow Methods for Modeling Bioactivity Data[深度学习：研究前馈深度神经网络超参数，并与浅层生物活性数据建模方法进行性能比较]
  Jun (Luke) Huan(KDD 2016研讨会) In recent years, research in Artificial Neural Networks (ANNs) has resurged, now under the Deep-Learning umbrella, and grown extremely popular due to ...
热度：6

2
Discovery of Functional Motifs from the Interface Region of Oligomeric Proteins using Frequent Subgraph Mining Method[从寡聚体蛋白质的界面区域发现功能基序]
  Mohammad Al Hasan(KDD 2016研讨会) Studying the interface region of a protein complex pavesthe way for understanding its dynamics and functionalities.Existing works study a protein inte...
热度：5

3
Multi-Task Label Propagation with Dissimilarity Measures[具有差异度量的多任务标签传播]
  Marco Frasca(KDD 2016研讨会) Multi-task algorithms typically use task similarity information as a bias to speed up learning. We argue that, when the classification problem is unba...
热度：5

4
Deep Learning for Connectomicss[用于连通性的深度学习]
  Shuiwang Ji(KDD 2016研讨会) The importance of research that aims to unlock the mystery of the human brain has recently been recognized worldwide. In January 2013, the European Un...
热度：5

5
Multiple network alignment via multiMAGNA++[通过multiMAGNA实现多网络对齐++]
  Vipin Vijayan(KDD 2016研讨会) Network alignment (NA) aims to find a node mapping between molecular networks of different species that identifies topologically or functionally simil...
热度：7

6
Improving Sentiment Classification of Social Media Posts through Data Refinements[通过数据精炼改进社交媒体帖子的情感分类]
  Vita Markman(KDD 2016研讨会) Quality training data is essential for building high performance machine learning models. However, certain types of tasks such as opinion mining are i...
热度：4

7
Actionable and Political Text Classification Using Word Embeddings and LSTM[使用词嵌入和LSTM进行可操作和政治文本分类]
  Adithya Rao(KDD 2016研讨会) In this work, we apply word embeddings and neural networks with Long Short-Term Memory (LSTM) to text classification problems, where the classificatio...
热度：4

8
Social Influence and Sentiment Analysis[社会影响与情感分析]
  Jie Tang(KDD 2016研讨会) Social influence is the behavioral change of a person because of the perceived relationship with other people, organizations and society in general. S...
热度：4

9
Visual Product Discovery[视觉产品发现]
  Phil Long(KDD 2016研讨会) We describe a system, Sentient Aware, that allows a user to interactively navigate through a catalog by viewing and clicking on images of products. Wh...
热度：11

10
Making an Idea Machine: Modular Architecture for a Scaleable Exploratory Data Analysis Platform in Genomics, Sports and Beyond[制造创意机器：基因组学、体育等领域可扩展探索性数据分析平台的模块化架构]
  Jesse Paquette(KDD 2016研讨会) Exploratory data analysis has been a core facilitator of discovery in genomics research over the last 20 years. The critical advancement in the field ...
热度：10