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Olivier Bachem

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Evaluating Generative Models Using Divergence Frontiers

May 26, 2019
Josip Djolonga, Mario Lucic, Marco Cuturi, Olivier Bachem, Olivier Bousquet, Sylvain Gelly

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Disentangling Factors of Variation Using Few Labels

May 03, 2019
Francesco Locatello, Michael Tschannen, Stefan Bauer, Gunnar Rätsch, Bernhard Schölkopf, Olivier Bachem

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High-Fidelity Image Generation With Fewer Labels

Mar 06, 2019
Mario Lucic, Michael Tschannen, Marvin Ritter, Xiaohua Zhai, Olivier Bachem, Sylvain Gelly

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Recent Advances in Autoencoder-Based Representation Learning

Dec 12, 2018
Michael Tschannen, Olivier Bachem, Mario Lucic

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Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations

Dec 02, 2018
Francesco Locatello, Stefan Bauer, Mario Lucic, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem

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Assessing Generative Models via Precision and Recall

Oct 28, 2018
Mehdi S. M. Sajjadi, Olivier Bachem, Mario Lucic, Olivier Bousquet, Sylvain Gelly

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Scalable k-Means Clustering via Lightweight Coresets

Jun 06, 2018
Olivier Bachem, Mario Lucic, Andreas Krause

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One-Shot Coresets: The Case of k-Clustering

Feb 20, 2018
Olivier Bachem, Mario Lucic, Silvio Lattanzi

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Practical Coreset Constructions for Machine Learning

Jun 04, 2017
Olivier Bachem, Mario Lucic, Andreas Krause

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Uniform Deviation Bounds for Unbounded Loss Functions like k-Means

Feb 27, 2017
Olivier Bachem, Mario Lucic, S. Hamed Hassani, Andreas Krause

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