Computer Science 692T - S-DistribtdMachLrng&DataMining

In this seminar, students will explore state-of-the-art techniques for finding patterns and functional relationships in data that is split across multiple locations. Topics include factorized learning for vertically partitioned data, model fitting via distributed stochastic gradient descent, and more. Students will read and present papers from a list provided by the instructors.

Open to Computer Science graduate students only. LECT 01=3 CR; LECT 02=1 CR. STUDENTS NEEDING INSTRUCTOR PERMISSION MUST REQUEST OVERRIDES VIA THE ON-LINE FORM: https://www.cics.umass.edu/overrides.