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Poster
Randomized PCA Algorithms with Regret Bounds that are Logarithmic in the Dimension
Manfred K. Warmuth · Dima Kuzmin
Author Information
Manfred K. Warmuth (Google Brain)
Dima Kuzmin
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2020 Poster: Reparameterizing Mirror Descent as Gradient Descent »
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2019 Workshop: Minding the Gap: Between Fairness and Ethics »
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2019 Poster: Robust Bi-Tempered Logistic Loss Based on Bregman Divergences »
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2018 Poster: Leveraged volume sampling for linear regression »
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2018 Spotlight: Leveraged volume sampling for linear regression »
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2017 Poster: Online Dynamic Programming »
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2017 Poster: Unbiased estimates for linear regression via volume sampling »
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2017 Spotlight: Unbiased estimates for linear regression via volume sampling »
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2014 Poster: The limits of squared Euclidean distance regularization »
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2014 Spotlight: The limits of squared Euclidean distance regularization »
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2013 Workshop: Large Scale Matrix Analysis and Inference »
Reza Zadeh · Gunnar Carlsson · Michael Mahoney · Manfred K. Warmuth · Wouter M Koolen · Nati Srebro · Satyen Kale · Malik Magdon-Ismail · Ashish Goel · Matei A Zaharia · David Woodruff · Ioannis Koutis · Benjamin Recht -
2012 Poster: Putting Bayes to sleep »
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2011 Poster: Learning Eigenvectors for Free »
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2010 Poster: Repeated Games against Budgeted Adversaries »
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2007 Spotlight: Boosting Algorithms for Maximizing the Soft Margin »
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2007 Poster: Boosting Algorithms for Maximizing the Soft Margin »
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