Fall 2016
CS 595J - Seminar on Secure Search
This seminar will study recent papers on security issues and algorithms for information retrieval and search. First organizational meeting will be on September 28th at 4:30pm in HFH 1152.
CS 291A/MAT 235: Computer Imaging
Note that the first class meeting will be on Tuesday, September 27.
CS 291A: Scalable Internet Services
This course explores advanced topics in highly scalable Internet services and their underlying systems architecture. Software today is increasingly being delivered as a service: accessible globally via web browsers and mobile applications and backed by millions of servers. Modern frameworks and platforms are making it easier to build and deploy these systems, such as Ruby on Rails and Amazon’s EC2.
CS 192 Computational Thinking
Topics
Data Representation
Representation of Text
Representation of Images and Video
Representation of Sound and Music
Storing and Accessing Data
Iteration
Recursion
Universal Computation
Arithmetic Algorithms
Searching and Sorting
Advanced Algorithms
Analytical versus Numerical
Symbolic Computation
Everyday Cryptography
CS 292F: Foundations of Data Science
This is new gradaute-level course on mathematical foundations of data science, based on the forthcoming book Foundations of Data Science by Avrim Blum, John Hopcroft and Ravi Kannan. The current draft of the book is available at http://www.cs.cornell.edu/jeh/book2016June9.pdf
The course will primarily focus on the following topics:
Geometry of high-dimensionsl space
Matrix methods
Machine learning
Clustering
Graph models
The course work will consist of both programming and theory projects.
CS 292F: Advanced Topics in Cryptography
This class is meant to open to you research in Cryptography, both theoretical and applied. To do so, the class will involve reading research papers, reviewing them, discussing them, and doing a project.
CS 595D AI safety and bias in machine learning
CS595D is a graduate computer science seminar that will explore topics
in AI safety and bias in machine learning. These are both fundamental
problems in AI research that have far more questions than answers.
Machine learning is currently deployed all over the world, classifying
data that impacts real people every single day. This year the EU passed
"right to explanation", a law that will take effect in 2018, and will
affect all companies that operate in Europe (yes Google, Facebook, etc).