The UC Santa Barbara NLP group studies the theoretical foundation and practical algorithms for language technologies. We tackle challenging learning and reasoning problems under uncertainty, and pursue answers via studies of machine learning, deep learning, and interdisciplinary data science. Broadly, we are interested in designing scalable inference and learning algorithms to analyze massive datasets with complex structures. In particular, our lab concentrates in the areas of information extraction, computational social science, knowledge graph, learning to reason, dialogue systems, language & vision, summarization, statistical relational learning, reinforcement learning, structure learning, and deep learning.

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