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- Rong-En Fan, Kai-Wei Chang, Cho-Jui Hsieh, Xiang-Rui Wang, Chih-Jen Lin
- Journal of Machine Learning Research
- 2008
LIBLINEAR is an open source library for large-scale linear classification. It supports logistic regression and linear support vector machines. We provide easy-to-use command-line tools and library… (More)
In many applications, data appear with a huge number of instances as well as features. Linear Support Vector Machines (SVM) is one of the most popular tools to deal with such large-scale sparse data.… (More)
- Guo-Xun Yuan, Kai-Wei Chang, Cho-Jui Hsieh, Chih-Jen Lin
- Journal of Machine Learning Research
- 2010
Large-scale linear classification is widely used in many are as. The L1-regularized form can be applied for feature selection; however, its non-different iability causes more difficulties in… (More)
The blind application of machine learning runs the risk of amplifying biases present in data. Such a danger is facing us with word embedding, a popular framework to represent text data as vectors… (More)
Efficient training of direct multi-class formulations of linear Support Vector Machines is very useful in applications such as text classification with a huge number examples as well as features.… (More)
- Yin-Wen Chang, Cho-Jui Hsieh, Kai-Wei Chang, Michael Ringgaard, Chih-Jen Lin
- Journal of Machine Learning Research
- 2010
Kernel techniques have long been used in SVM to handle linear ly inseparable problems by transforming data to a high dimensional space, but training and te sting large data sets is often time… (More)
- Hsiang-Fu Yu, Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin
- IJCAI
- 2010
Recent advances in linear classification have shown that for applications such as document classification, the training can be extremely efficient. However, most of the existing training methods are… (More)
Methods for learning to search for structured prediction typically imitate a reference policy, with existing theoretical guarantees demonstrating low regret compared to that reference. This is… (More)
- Kai-Wei Chang, Cho-Jui Hsieh, Chih-Jen Lin
- Journal of Machine Learning Research
- 2008
Linear support vector machines (SVM) are useful for classifying large-scale sparse data. Problems with sparse features are common in applications such as document classification and natural language… (More)
- Kai-Wei Chang, Wen-tau Yih, Bishan Yang, Christopher Meek
- EMNLP
- 2014
While relation extraction has traditionally been viewed as a task relying solely on textual data, recent work has shown that by taking as input existing facts in the form of entity-relation triples… (More)