We empirically study the relationship between supervised and multiple instance (MI) learning. Algorithms to learn various concepts have been adapted to the MI representation. Howe...
We present a novel approach for structure prediction that addresses the difficulty of obtaining labeled structures for training. We observe that structured output problems often h...
Ming-Wei Chang, Vivek Srikumar, Dan Goldwasser, Da...
The goal of semi-supervised learning (SSL) methods is to reduce the amount of labeled training data required by learning from both labeled and unlabeled instances. Macskassy and Pr...
Semi-supervised learning plays an important role in the recent literature on machine learning and data mining and the developed semisupervised learning techniques have led to many...
Zhen Guo, Zhongfei (Mark) Zhang, Eric P. Xing, Chr...
Abstract. This paper presents a machine learning approach for paraphrase identification which uses lexical and semantic similarity information. In the experimental studies, we exam...