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Course Criteria
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3.00 Credits
Current and emerging research topics in communication networks: network protocols, network measurement, internet routing, network security, adhoc and sensor networks, disruption tolerant networks. Lecture, readings, and discussion, plus a project. Prerequisites: CSE 342 or CSE 404, and Math 231, or permission of instructor.
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3.00 Credits
Bayesian decision theory and the design of parametric and nonparametric classifiers: linear (perceptrons), quadratic, nearest-neighbors, neural nets. Machine learning techniques: boosting, bagging. High-performance machine vision systems: segmentation, contextual analysis, adaptation. Students carry out projects, e.g. on digital libraries and vision-based Turing tests. This course, a version of 326 for graduate students requires advanced assignments. Credit will not be given for both CSE 326 and CSE 426. Prerequisites: CSE 109, CSE 340, Math 205, Math 231, or consent of instructor.
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3.00 Credits
Theory, architecture and applications of the Semantic Web. Issues in designing distributed knowledge representation languages, ontology development, knowledge acquisition, scalable reasoning, integrating heterogeneous data sources, and web-based agents.
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3.00 Credits
Software and technology of virtual environment systems. Current research in virtual environments. User tracking, display, and view rendering hardware. VE application programming libraries, real-time rendering techniques, 3D model representations, networking systems for distributed and multi-user environments, 3D user interaction techniques.
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3.00 Credits
Theory and algorithms for topics in textual data mining and statistical natural language processing (NLP). Fundamental mathematics and linguistics of statistical NLP; probability theory and information theory. Text mining algorithms and applications. Practical design, implementation, application and evaluation of statistical NLP and textual data mining techniques in class projects. Prerequisite: CSE 347
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3.00 Credits
Principles of rational autonomous software systems. Agent theory; agent architectures, including logic-based, utilitybased, practical reasoning, and reactive; multiagent systems; communication languages; coordination methods including negotiation and distributed problem solving; applications. Prerequisite: CSE 327 or equivalent.
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3.00 Credits
Design and construction of modular, reusable, extensible and portable software using statically typed object-oriented programming languages (Eiffel, C++, Objective C). Abstract data types; genericity; multiple inheritance; use and design of soft-ware libraries; persistence and object-oriented databases; impact of object-oriented programming on the software life cycle.
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3.00 Credits
AI techniques used to build IDSSs: case-based reasoning, decision trees and knowledge representation. Applications: help-desk systems, e-commerce, and knowledge management. This course, a version of 335 for graduate students, requires research projects and advanced assignments. Credit will not be given for both CSE 335 and CSE 435.
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3.00 Credits
Design and description of software architecture for large systems. Current research topics in software architecture. Individual projects are a significant part of this course. Projects may include the design of a new architecture, reverse engineering the architecture of an existing system, or investigation of a research topic in software architecture. Prerequisite: CSE 216 or CSE 432 or consent of the instructor.
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3.00 Credits
Fundamental concepts of and algorithms for graphs, including: connectivity, planarity, network flows, matchings, colorings, traversals, duality, intractability and applications. Prerequisite: CSE 340 or consent of instructor.
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