Tuesday, September 5th @ 11:00-12:30 PM (639 Evans Hall)
Sparse Low-Rank Dictionary Learning
Robert Anderson, UC Berkeley
Sparse Dictionary Learning (SDL) can be used to extract narrow factors driving stock returns from a stock returns matrix, provided the returns are generated by sparse factors alone. We describe progress on a variant called Sparse Low-Rank Dictionary Learning (SLRDL), designed to simultaneously extract broad and narrow factors for the returns matrix, when the returns are generated by both types of factors.