printer friendly pageCS 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.
Last offered: Spring 2005
| Repeatable
for 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.
Terms: Spr
| Units: 3
Instructors:
Plotkin, S. (PI)
CS 369M: Algorithms for Modern Massive Data Set Analysis
Algorithmic and statistical methods for large-scale data analysis: matrix and graph algorithms; strengths and weaknesses of theoretical techniques for practical scientific and Internet data analysis; overlap with related problems in statistics, optimization, numerical analysis, and machine learning. Representative topics: matrix problems (numerical and statistical perpectives; algorithmic approaches, including Johnson-Lindenstrauss lemma and randomized projection and sampling algorithms; novel matrix factorizations); graph problems (graph partitioning algorithms, including spectral methods, flow-based methods, and recent geometric methods; local graph algorithms and approximate eigenvector computation); and applications to machine learning and statistical data analysis (motivating applications; algorithmic basis of the RKHS method; geometric data analysis, regularization, and statistical inference; boosting and its relationships to conjugate gradient methods, duality, convexity, online learning, and approximation algorithms). Implementing these ideas in medium and large-scale applications. Prerequisites: algorithms such as
CS 161, linear algebra such as
MATH 51, and probability theory such as
CS 109, or equivalents.
Instructors:
Mahoney, M. (PI)
CS 369N: Novel Paradigms for Algorithmic Analysis
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: Aut
| Units: 3
Instructors:
Roughgarden, T. (PI)
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
Interactive systems, research areas in interaction techniques, and the design, prototyping, and evaluation of user interfaces. Topics: computer-supported cooperative work; audio, speech, and multimodal interfaces; user interface toolkits; design and evaluation methods; ubiquitous and context-aware computing; tangible interfaces, haptic interaction; and mobile interfaces.
Terms: Spr
| Units: 3
| Repeatable
for credit
Instructors:
Klemmer, S. (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 377L: Learning in a Networked World (EDUC 298)
Foundations, theories and empirical studies for interdisciplinary advances in how we conceive of the potentials and challenges associated with lifelong, lifewide and life-deep learning in a networked world given the growth of always-on cyberinfrastructure for supporting information and social networks across space and time with personal computers, netbooks, and mobiles.
Terms: Spr
| Units: 3
Instructors:
Pea, R. (PI)
CS 377V: Creating Health Habits with Social and Mobile Technologies
How to create habits in people via social and mobile tech. Design methods and psychological principles for long-term change. Focus on health behaviors. First, teams analyze best-in-class habit technologies. Next, teams create and test their own solutions for habit formation, leveraging Facebook, texting, and other platforms. No coding required.
Terms: Win, Spr
| Units: 3
| Repeatable
11 times
(up to 33 units total)
Instructors:
Fogg, B. (PI)
CS 378: Phenomenological Foundations of Cognition, Language, and Computation
Critical analysis of theoretical foundations of the cognitive approach to language, thought, and computation. Contrasts of the rationalistic assumptions of current linguistics and artificial intelligence with alternatives from phenomenology, theoretical biology, critical literary theory, and socially-oriented speech act theory. Emphasis is on the relevance of theoretical orientation to the design, implementation, and impact of computer systems as it affects human-computer interaction.
Terms: Aut
| Units: 3-4
Instructors:
Winograd, T. (PI)
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