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181 - 190 of 215 results for: CS

CS 349: Topics in Programming Systems

Advanced material is often taught for the first time as a topics course, perhaps by a faculty member visiting from another institution. May be repeated for credit.
Terms: offered occasionally | Units: 3 | Repeatable for credit | Grading: Letter or Credit/No Credit

CS 349C: Topics in Programming Systems: Readings in Distributed Systems

Discussion of research publications that are of current interest in distributed systems. Students are expected to read all papers, and sign up for presentation of one paper. The course itself is 1 unit. Those interested in working on a project along with the readings should enroll for 3 units.
Terms: not given this year | Units: 1-3 | Grading: Letter or Credit/No Credit

CS 358: Topics in Programming Language Theory

Topics of current research interest in the mathematical analysis of programming languages, structured operational semantics, domain theory, semantics of concurrency, rich type disciplines, problems of representation independence, and full abstraction. See Time Schedule or Axess for current topics. May be repeated for credit. Prerequisites: 154, 157, 258, or equivalents. (Staff)
Terms: offered occasionally | Units: 3 | Repeatable for credit | Grading: Letter or Credit/No Credit

CS 359: Topics in the Theory of Computation

Advanced material is often taught for the first time as a topics course, perhaps by a faculty member visiting from another institution. May be repeated for credit.
Terms: offered occasionally | Units: 3 | Repeatable for credit | Grading: Letter or Credit/No Credit

CS 361A: Advanced Algorithms

Advanced data structures: union-find, self-adjusting data structures and amortized analysis, dynamic trees, Fibonacci heaps, universal hash function and sparse hash tables, persistent data structures. Advanced combinatorial algorithms: algebraic (matrix and polynomial) algorithms, number theoretic algorithms, group theoretic algorithms and graph isomorphism, online algorithms and competitive analysis, strings and pattern matching, heuristic and probabilistic analysis (TSP, satisfiability, cliques, colorings), local search algorithms. May be repeated for credit. Prerequisite: 161 or 261, or equivalent.
Terms: not given this year | Units: 3 | Repeatable for credit | Grading: Letter or Credit/No Credit

CS 361B: Advanced Algorithms

Topics: fundamental techniques used in the development of exact and approximate algorithms for combinational optimization problems such as generalized flow, multicommodity flow, sparsest cuts, generalized Steiner trees, load balancing, and scheduling. Using linear programming, emphasis is on LP duality for design and analysis of approximation algorithms; interior point methods for LP. Techniques for development of strongly polynomial algorithms. Prerequisites: 161 or 261, or equivalent.
Terms: not given this year | Units: 3 | Grading: Letter or Credit/No Credit

CS 364A: Algorithmic Game Theory

Topics at the interface of computer science and game theory such as: algorithmic mechanism design; combinatorial auctions; computation of Nash equilibria and relevant complexity theory; congestion and potential games; cost sharing; game theory and the Internet; matching markets; network formation; online learning algorithms; price of anarchy; prior-free auctions; selfish routing; sponsored search. Prerequisites: 154N and 161, or equivalents.
Terms: not given this year | Units: 3 | Grading: Letter or Credit/No Credit

CS 369: Topics in Analysis of Algorithms

Advanced material is often taught for the first time as a topics course, perhaps by a faculty member visiting from another institution. May be repeated for credit.
Terms: offered occasionally | Units: 3 | Repeatable for credit | Grading: Letter or Credit/No Credit

CS 371: Computational Biology in Four Dimensions (BIOMEDIN 371, BIOPHYS 371, CME 371)

Computational approaches to understanding the three-dimensional spatial organization of biological systems and how that organization evolves over time. The course will cover cutting-edge research in both physics-based simulation and computational analysis of experimental data, at scales ranging from individual molecules to entire cells. Prerequisite: CS 106A or equivalent, and an introductory course in biology or biochemistry. Recommended: some experience in mathematical modeling (does not need to be a formal course).
Terms: not given this year | Units: 3 | Grading: Letter or Credit/No Credit

CS 377: Topics in Human-Computer Interaction

Contents change each quarter. May be repeated for credit. See http://hci.stanford.edu/academics for offerings.
Terms: offered occasionally | Units: 2-3 | Repeatable for credit | Grading: Letter or Credit/No Credit
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