Special Topics Course

This is a graduate-level course on neural network and deep learning.  We will discuss neural network, deep learning,  CNN,  RNN, LSTM and their newest advances. 

This course covers advanced topics on information retrieval, web search, and related scalable information systems. The topics include search engines and advertisements, web crawling, classification, indexing and data serving, ranking and recommendation, user behavior analysis, and online services. This course will also cover system and middleware support for building related large-scale Internet services.

Topics:

Public-key cryptography was conceived in 1976 by Whitfield Diffie and Martin Hellman. The first practical realization followed in 1977 when Ron Rivest, Adi Shamir and Len Adleman proposed their now well-known RSA cryptosystem, in which security is based on the intractability of the integer factorization problem. Elliptic curve cryptography (ECC) was discovered in 1985 by Neal Koblitz and Victor Miller. Elliptic curve cryptographic schemes are public-key mechanisms that provide the same functionality as RSA schemes.

Note that the first class meeting will be on Tuesday, September 27.
 

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.

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
 

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.

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.

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.