My research interests are primarily machine learning with application interests in natural language processing tasks. More specifically, machine learning scenarios where there is interaction with a domain expert (active learning, interactive knowledge acquisition), utilization of unlabeled data, and interdependencies between learned classifiers.

Some publications:

• Alexandre Klementiev, Dan Roth, and Kevin Small. Unsupervised Rank Aggregation with Distance-based Models. In Proc. of the International Conference on Machine Learning (ICML), 2008.
• Dan Roth and Kevin Small. Active Learning for Pipeline Models. In Proceedings of the National Conference on Artificial Intelligence (AAAI), 2008.
• Alexandre Klementiev, Dan Roth, and Kevin Small. An Unsupervised Learning Algorithm for Rank Aggregation. In Proc. of the European Conference on Machine Learning (ECML), 2007.
• Paul Davis, Kevin Small, and Zhuli Xie. All Links are not the Aame: Evaluating Word Alignments for Statistical Machine Translation. In Proc. of the Machine Translation Summit, 2007.
• Dan Roth and Kevin Small. Margin-based Active Learning for Structured Output Spaces. In Proc. of the European Conference on Machine Learning (ECML), 2006.
• Dan Roth and Kevin Small. Active Learning with Perceptron for Structured Output. In Proc. of the ICML Workshop on Learning in Structured Output Spaces, 2006.
• Xin Li, Dan Roth, and Kevin Small. The Role of Semantic Information in Learning Question Classifiers. In Proc. of the International Joint Conference on Natural Language Processing (IJCNLP), 2004.
• Dan Roth, Chad Cumby, Xin Li, Paul Morie, Ramya Nagarajan, Nick Rizzolo, Kevin Small, and Wentau Yih. Question Answering Via Enhanced Understanding of Questions. In Text Retrieval Conference (TREC), 2002.