58600 Learnability

Instructor
Greg Kobele; email
Time and location
MW 1:30PM-2:50PM, Rosenwald 208

Two of the main problems concerning language include how we use language, and how we learn to so do. Most work in linguistics explicitly concerns itself with the first question, at various levels of abstraction. Still, even here, considerations of learnability are often implicitly appealed to in theory construction. Outside of linguistics, in the domain of natural language processing, it has become recognized as practically impossible to hand craft wide coverage grammars, and much energy has been devoted to their automatic induction from raw data.
This course is devoted to understanding the literature on grammatical inference, especially as it pertains to learning linguistic structures from data. We will be primarily interested in matters of principle: under which conditions can we guarantee that a learner will acquire a grammar with which kind of relation to the input; and only secondarily in matters of practice: how provably correct algorithms can serve as the foundation for practical learning systems.
We study two of the most influential learning paradigms, the categorical Gold paradigm and the stochastic PAC, with attention to how they can inform our ideas about how humans learn language, and thus about grammar.

Class Material

Schedule Lecture schedule
Resources Other course resources

Course Information

Lectures MW 1:30-2:50, RO 208
Office Hours by appointment
Notes Notes and papers will be handed out.
Grading
  • 50% Participation
  • 20% Private discussion of final topic (7th week)
  • 30% Final.
Exams A final paper will be due after finals week

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