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

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  • UserDr Nicolas Flammarion
  • ClockMonday 26 November 2018, 14:00-15:00
  • HouseCMS, MR11.

If you have a question about this talk, please contact J.W.Stevens.

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.

This talk is part of the CCIMI Seminars series.

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