IE 598

Spring 2016 Part of Term 1

Part of Term 1
Jan 19-May 4

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.

Section Status updates every 10 minutes.
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
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
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
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
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
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.
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