LING 506

Spring 2022 Part of Term 1

Part of Term 1
Jan 18-May 4

Topics in Computational Ling

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Credit: 4 hours.

Provides an introduction to practical problems in computational linguistics in a laboratory setting. At the beginning of the semester, a substantial project will be assigned to the class, and the class will work as a team towards implementing a solution, and evaluating the final product against a test corpus, which will also be developed during the class. Topical readings will also be assigned and will be discussed.

Approved for letter or S/U grading. May be repeated in more than one section per term to a maximum of 8 hours, if topics vary; may be repeated in subsequent terms to a maximum of 12 hours, if topics vary. Prerequisite: LING 406, and an introductory level Computer Science programming course, or consent of instructor.

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LING 506 class schedule data for spring 2022
	CRN	Type	Section	Time	Day	Location	Instructor	Section Details
	36523	Lecture-Discussion	E	11:00AM -12:20PM	TR	G13 Foreign Languages Building	Tang, Y	Part of Term: 1 Date Range: 01/18/22-05/04/22 Section Title: Introductory Machine Learning Section Info: Topic: Introductory Machine Learning. Description: Machine learning has been thriving in many areas for both research and industry. It offers solutions to problems that traditional approaches may not be able to deal with or fall short in efficiency. From supervised to unsupervised learning, this course is set to give students a broad understanding in modern machine learning methods and techniques. During the course, students are expected to acquire knowledge and skills in solving practical problems in clustering and classification, using techniques such as k-means, Gaussian mixture models, decision trees, support vector machines and neural networks. This course requires LING490 or equivalent in programming and understanding in probability and statistics as prerequisite. Prerequisites: LING 406 or LING 490
	72382	Lecture-Discussion	GDP	11:00AM -12:20PM	TR	G3 Foreign Languages Building	Del Pinal, G	Part of Term: 1 Date Range: 01/18/22-05/04/22 Section Title: Computational Semantics Section Info: Topic: Computational Semantics This course will focus on computational accounts of core semantic and pragmatic phenomena in natural languages. It will include a preliminary introduction to lambda calculus, compositionality and higher-order logic. We will then discuss the semantics of various functional and logical terms and phrases of natural languages---quantifiers (`most’, `some’), connectives (`and’, `or’), modals (`possible’, `must’, `likely’), polarity-sensitive items (`any’)---and the semantics of questions, question-answer systems, discourse representation, selection of variables, and logical, probabilistic and pragmatic/common-sense inferences in natural languages. We will also introduce some standard and more recent computational models of the open class lexicon (words like `table’, `tigers’ ) and discuss the ways in which recent computational models of the lexicon advance our understanding of the interface between language and world knowledge/general cognition. For each topic, we will first introduce the relevant facts and standard approaches from formal semantics, using references such as Heim & Kratzer (1998), and will then explore the advantages and challenges of taking a computational perspective. Most assignments for the course will be done in Haskell, and the main textbook---which presupposes no familiarity with Haskell, will be Eijck and Unger (2010), Computational Semantics.