Gen-Oja: A Simple and Efficient Algorithm for Streaming Generalized Eigenvector Computation

In this talk, we study the problems of principal Generalized Eigenvector computation and Canonical Correlation Analysis in the stochastic setting. We propose a simple and efficient algorithm, Gen-Oja, for these problems. We prove the global convergence of our algorithm, borrowing ideas from the theory of fast-mixing Markov chains and two-time-scale stochastic approximation, showing that it achieves the optimal rate of convergence.

• Speaker: Dr Nicolas Flammarion
• Monday 26 November 2018, 14:00–15:00
• Venue: CMS, MR11.
• Series: CCIMI Seminars; organiser: J.W.Stevens.