Fields: machine learning, natural language processing.
Topics: unsupervised learning, structured prediction, statistical learning theory, grounded language acquisition, compositional semantics, program induction.
Learning semantics: Natural language allows us to express complex ideas using a few words, but the actual semantics are rarely directly observed. We therefore model the expressive semantics of language as programs whose execution produces observed data, and develop algorithms to learn these programs from indirect supervision.
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