Syllabus

Course Info

Instructor: Quanquan Liu
Meeting times: MW 11:30am - 12:50pm

Other Courses

A (certainly not comprehensive) list of other courses with course materials (notes/papers/presentations), sorted roughly by topic. Please email about additional courses that should be listed!

Parallel Graph Algorithms

Graph Analytics (Julian Shun, MIT)
Parallel and Concurrent Algorithms (Guy Blelloch, CMU)
Scalable Parallel Algorithms and Data Structures (Laxman Dhulipala, UMD)
Parallel and Sequential Algorithms (Kunal Agrawal and I-Ting Angelina Lee, WashU)

Distributed Graph Algorithms

Massively Parallel Algorithms (Mohsen Ghaffari, MIT)
Distributed Algorithms (Mohsen Ghaffari and Nancy Lynch, MIT)
Massively Parallel Computation (Slobodan Mitrović, UC Davis)
Distributed Graph Algorithms(David Peleg and Merav Parter, Weizmann)

Sublinear and Streaming Algorithms

Algorithmic Techniques for Massive Data (Alexandr Andoni, Columbia)
Algorithms for Big Data (David Woodruff, CMU)
Sublinear Time Algorithms (Ronitt Rubinfeld, MIT)
Graph Streaming Algorithms and Lower Bounds (Sepehr Assadi, UWaterloo)
Sublinear Algorithms (Sofya Raskhodnikova, BU)
Sketching Algorithms for Big Data (Piotr Indyk, MIT, and Jelani Nelson, UC Berkeley)
Data Streams Algorithms (Andrew McGregor, UMass Amherst)

Learning-Augmented (Algorithms with Predictions) Algorithms

Learning-Augmented Algorithms (Piotr Indyk, MIT)

Differential Privacy

Privacy in Statistics and Machine Learning (Adam Smith, BU, and Jonathan Ullman, Northeastern)
Algorithmic Foundations of Data Privacy (Aaron Roth, UPenn)
Foundations of Data Privacy (Rachel Cummings, Columbia)
Algorithms for Private Data Analysis (Gautam Kamath, UWaterloo)

Practical Implementations and Systems

Algorithm Engineering (Julian Shun, MIT)
Mining of Massive Datasets (Jure Leskovec, Anand Rajaraman, Jeff Ullman, Stanford)