Lectures: Tue/Thu 12:30pm–1:45pm in MCB 240
Instructor: Ali Vakilian (Office Hours: Wed 11am–12pm in TORG 3120)
Instructor: Ali Vakilian (Office Hours: Wed 11am–12pm in TORG 3120)
Description: Modern research in machine learning, operations research and large-scale scientific computing often deals with data too large to store or process directly. This course introduces rigorous, space-efficient algorithms for massive data sets, including streaming and sketching, dimensionality reduction, scalable numerical linear algebra and graph algorithms. Students will explore recent advances and develop the background needed for research in big-data algorithms. Check the syllabus for more details.
Prerequisites: CS 4100 or equivalent, or consent of the instructor. Familiarity with basic probability and linear algebra is expected.
Credits: 3
Credits: 3