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Background
- Research focuses on the computational foundations of intelligent behavior, with learning at the core of intelligence.
- Centers on machine learning and inference methods to facilitate natural language understanding.
- Recent focus on constrained conditional models using integer linear programming for joint learning and global inference.
- Explores fundamental issues such as learning with indirect supervision, response-driven learning, decomposed learning, and amortized inference.
- Emphasizes 'incidental supervision' as a strategy to circumvent annotation challenges in complex tasks.
- Also works on natural language acquisition, ESL, and information trustworthiness.
Co-authors: 0 (list not available)