IE 598

Spring 2016 All Classes

All Classes

Special Topics

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Credit: 1 TO 4 hours.

Subject offerings of new and developing areas of knowledge in industrial engineering intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites.

Approved for letter and S/U grading. May be repeated in the same or separate terms if topics vary.

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IE 598 class schedule data for spring 2016
CRN	Type	Section	Time	Day	Location	Instructor	Section Details
64374	Lecture	ADA	3:30PM -4:50PM	TR	204 Transportation Building	Sreenivas, R	Part of Term: 1 Date Range: 01/19/16-05/04/16 Credit: 3 hours Section Title: Algorithms for Data Analysis Section Info: Prerequisites: CS 225 or equivalent; IE 411 or equivalent. This course will introduce the student to a set of algorithms for Data Analytics. Hashing, Indexes, Caching. Algorithms for structured datasets. Streaming Data models. PageRank algorithms. Algorithms for Market-Basket models. Clustering algorithms. Case Studies.
38950	Lecture-Discussion	AI	12:30PM -1:50PM	TR	243 Mechanical Engineering Bldg	Oh, S	Part of Term: 1 Date Range: 01/19/16-05/04/16 Credit: 3 hours Section Title: Algorithms for Inference Section Info: Prerequisites: Introductory, graduate-level Probability and Linear Algebra. This is a special topics course on algorithms for inference problems with emphasis on the theoretical analyses. Topics include tensor methods, matrix factorization, matrix completion, rank aggregation, and sparse recovery.
64362	Lecture-Discussion	DO	11:00AM -12:20PM	TR	106B1 Engineering Hall	Nedich, A	Part of Term: 1 Date Range: 01/19/16-05/04/16 Credit: 4 hours Section Title: Distributed Optimization Section Info: Prerequisite: basic course in linear algebra, real analysis, and probability theory. This course is focused on large scale systems and distributed computational models for optimization in such systems. The models will include applications in communications and sensory systems. The optimization tools would span algorithms from convex programming as well as the approaches from game theory.
60582	Lecture	LM	12:30PM -1:50PM	TR	206 Transportation Building	Marla, L	Part of Term: 1 Date Range: 01/19/16-05/04/16 Credit: 4 hours Section Title: Special Topics Course Section Info: Optimization Methods for Large-Scale, Network-Based Systems Description: Students will study models and solution algorithms with focus on large-scale, networked systems. Students will use examples from applications such as transportation, communication, scheduling, etc. Topics covered will include lagrangean relaxation, multi-commodity flows, branch-and-price-and-cut, etc.
64238	Lecture-Discussion	SDP	2:00PM -4:50PM	F	1103 Siebel Center for Comp Sci	Chen, X	Part of Term: 1 Date Range: 01/19/16-05/04/16 Credit: 4 hours Section Title: Stochastic Dynamic Programming Section Info: Prerequisites: IE 411, IE 410 or equivalent. The course covers the basic models and solution techniques for problems of sequential decision making under uncertainty. We introduce discrete and continuous time models with finite and infinite planning horizon. Applications are drawn from economics, finance, operations management and engineering.