printer friendly pageCS 364B: Topics in Algorithmic Game Theory
Topics on the interface of computer science and game theory. May be repeated for credit. Prerequisites: 364A or instructor permission.
Terms: Win
| Units: 3
| Repeatable
for credit
Instructors:
Roughgarden, T. (PI)
CS 367: Algebraic Graph Algorithms
Due to the surprisingly fast algorithms for the problem, matrix multiplication is routinely used as nna basic building block for algorithms beating the brute-force approach. This course explores a variety of problems, mostly within graph algorithms, that can be solved faster using a fast matrix multiplication algorithm. Topics include: Graph Transitive Closure, All Pairs Shortest Paths, Perfect Matching, Minimum Cycle, Finding Cliques, and a variety of equivalences between problems involving matrix multiplication. Prerequisites: 154, 161, or the equivalent mathematical maturity.
Terms: Spr
| Units: 3
Instructors:
Williams, V. (PI)
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.
Last offered: Spring 2013
| Repeatable
for credit
CS 371: Computational Biology in Four Dimensions (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: Spr
| Units: 3
Instructors:
Dror, R. (PI)
CS 373: Statistical and Machine Learning Methods for Genomics (BIO 268, BIOMEDIN 245, GENE 245, STATS 166, STATS 345)
Computational algorithms for human genetics research. Topics include: permutation, bootstrap, expectation maximization, hidden Markov model, and Markov chain Monte Carlo. Rationales and techniques illustrated with existing implementations commonly used in population genetics research, disease association studies, and genomics analysis. Prerequisite:
GENE 244 or consent of instructor
CS 374: Algorithms in Biology (BIOMEDIN 374)
Algorithms and computational models applied to molecular biology and genetics. Topics vary annually. Possible topics include biological sequence comparison, annotation of genes and other functional elements, molecular evolution, genome rearrangements, microarrays and gene regulation, protein folding and classification, molecular docking, RNA secondary structure, DNA computing, and self-assembly. May be repeated for credit. Prerequisites: 161, 262 or 274, or BIOCHEM 218, or equivalents.
Terms: Spr
| Units: 2-3
Instructors:
Batzoglou, S. (PI)
CS 376: Research Topics in Human-Computer Interaction
Prepares students to conduct original HCI research by reading and discussing seminal and cutting-edge research papers. Main topics are ubiquitous computing, social computing, and design and creation; breadth topics include HCI methods, programming, visualization, and user modeling. Student pairs perform a quarter-long research project. For undergraduates, CS147 is a prerequisite.
Terms: Spr
| Units: 3-4
| Repeatable
for credit
Instructors:
Bernstein, M. (PI)
CS 377: Topics in Human-Computer Interaction
Contents change each quarter. May be repeated for credit. See
http://hci.stanford.edu/academics for offerings.
| Repeatable
for credit
CS 377D: Topics in Learning and Technology: d.compress - Designing Calm (EDUC 328A)
Contents of the course change each year. The course can be repeated. Stress silently but steadily damages physical and emotional well-being, relationships, productivity, and our ability to learn and remember. This highly experiential and project-oriented class will focus on designing interactive technologies to enable calm states of cognition, emotion, and physiology for better human health, learning, creativity and productivity.
Terms: Spr
| Units: 2-3
| Repeatable
6 times
(up to 18 units total)
CS 377W: HCI Issues in Wearable Computing
With devices like Pebble and Google Glass moving from labs to consumer use, Wearable Computing represents the forefront of HCI innovation. In this course, students will engage with a broad range of issues around the design and development of wearable devices and systems and develop their own wearable interaction. The course begins with use, analysis, and redesign of an existing wearable, followed by a larger group project integrating concepts from the course to prototype a novel wearable interaction. Students work in project teams, prototyping their wearable concept and communicating their progress through demonstration, final report, and presentation. Google Glass will be available for students interested in experimenting with this platform. Prerequisites: One of the following:
CS 147 or
CS 247.
Terms: Spr
| Units: 3
Instructors:
Ashbrook, D. (PI)
;
White, S. (PI)
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