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101 - 110 of 154 results for: MS&E

MS&E 321: Stochastic Systems

Topics in stochastic processes, emphasizing applications. Markov chains in discrete and continuous time; Markov processes in general state space; Lyapunov functions; regenerative process theory; renewal theory; martingales, Brownian motion, and diffusion processes. Application to queueing theory, storage theory, reliability, and finance. Prerequisites: 221 or STATS 217; MATH 113, 115. (Glynn)
Terms: Spr | Units: 3 | Grading: Letter or Credit/No Credit

MS&E 322: Stochastic Calculus and Control

Ito integral, existence and uniqueness of solutions of stochastic differential equations (SDEs), diffusion approximations, numerical solutions of SDEs, controlled diffusions and the Hamilton-Jacobi-Bellman equation, and statistical inference of SDEs. Applications to finance and queueing theory. Prerequisites: 221 or STATS 217: MATH 113, 115.
Terms: Spr | Units: 3 | Grading: Letter or Credit/No Credit
Instructors: Glynn, P. (PI)

MS&E 324: Stochastic Methods in Engineering (CME 308, MATH 228)

The basic limit theorems of probability theory and their application to maximum likelihood estimation. Basic Monte Carlo methods and importance sampling. Markov chains and processes, random walks, basic ergodic theory and its application to parameter estimation. Discrete time stochastic control and Bayesian filtering. Diffusion approximations, Brownian motion and an introduction to stochastic differential equations. Examples and problems from various applied areas. Prerequisites: exposure to probability and background in analysis.
Terms: Spr | Units: 3 | Grading: Letter or Credit/No Credit
Instructors: Glynn, P. (PI)

MS&E 325: Advanced Topics in Applied Probability

Current stochastic models, motivated by a wide range of applications in engineering, business, and science, as well as the design and analysis of associated computational methods for performance analysis and control of such stochastic systems.
Terms: Win | Units: 3 | Grading: Letter or Credit/No Credit

MS&E 326: Advanced Topics in Game Theory with Engineering Applications

Advanced Topics in Game Theory with Engineering Applications
Terms: not given this year, last offered Spring 2018 | Units: 3 | Repeatable for credit | Grading: Letter or Credit/No Credit

MS&E 330: Law, Order & Algorithms (CSRE 230, SOC 279)

Data and algorithms are transforming law enforcement and criminal justice, a shift that is ripe for rigorous empirical and narrative exploration. This class is centered around several data-driven projects in criminal justice, with the goal of fostering greater understanding, transparency, and public accountability. Students work in interdisciplinary teams, using a combination of statistical and journalistic methods. Some of the work may be published by news organizations or may be used to advance data journalism investigations. Students with a background in statistics, computer science, law, public policy or journalism are encouraged to participate. Enrollment is limited, and project teams will be selected during the first week of class.
Terms: Spr | Units: 3 | Grading: Letter (ABCD/NP)
Instructors: Goel, S. (PI)

MS&E 332: Topics in Social Algorithms

In depth discussion of selected research topics in social algorithms, including networked markets, collective decision making, recommendation and reputation systems, prediction markets, social computing, and social choice theory. The class will include a theoretical project and a paper presentation. Prerequisites: CS 261 or equivalent; understanding of basic game theory.
Terms: Spr | Units: 3 | Grading: Letter or Credit/No Credit
Instructors: Goel, A. (PI)

MS&E 333: Social Algorithms

This seminar will introduce students to research in the field of social algorithms, including networked markets, collective decision making, recommendation and reputation systems, prediction markets, social choice theory, and models of influence and contagion.
Terms: not given this year, last offered Spring 2015 | Units: 1 | Grading: Satisfactory/No Credit

MS&E 334: Topics in Social Data

This course provides a in-depth survey of methods research for the analysis of large-scale social and behavioral data. There will be a particular focus on recent developments in discrete choice theory and preference learning. Connections will be made to graph-theoretic investigations common in the study of social networks. Topics will include random utility models, item-response theory, rank aggregation, centrality and ranking on graphs, and random graphs. The course is intended for Ph.D. students, but masters students interested in research topics are welcome. Recommended: 221, 226, CS161, or equivalents.
Terms: Aut | Units: 3 | Grading: Letter or Credit/No Credit

MS&E 335: Queueing and Scheduling in Processing Networks

Advanced stochastic modeling and control of systems involving queueing and scheduling operations. Stability analysis of queueing systems. Key results on single queues and queueing networks. Controlled queueing systems. Dynamic routing and scheduling in processing networks. Applications to modeling, analysis and performance engineering of computing systems, communication networks, flexible manufacturing, and service systems. Prerequisite: 221 or equivalent.
Terms: not given this year, last offered Autumn 2015 | Units: 3 | Grading: Letter or Credit/No Credit
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