Mario Lucic - RankMe

97 papers A* 33A 5Journal 52Unranked 6

Year	Rank	Type	Title / Venue / Authors
2024	A*	`conf`	End-to-End Spatio-Temporal Action Localisation with Video Transformers. CVPR Alexey A. Gritsenko, Xuehan Xiong, Josip Djolonga, Mostafa Dehghani, Chen Sun, Mario Lucic, Cordelia Schmid, Anurag Arnab
2024	A*	`conf`	On Scaling Up a Multilingual Vision and Language Model. CVPR Xi Chen, Josip Djolonga, Piotr Padlewski, Basil Mustafa, Soravit Changpinyo, Jialin Wu, Carlos Riquelme Ruiz, Sebastian Goodman, Xiao Wang, Yi Tay, Siamak Shakeri, Mostafa Dehghani, Daniel Salz, Mario Lucic, Michael Tschannen, Arsha Nagrani, Hexiang Hu, Mandar Joshi, Bo Pang, Ceslee Montgomery, Paulina Pietrzyk, Marvin Ritter, A. J. Piergiovanni, Matthias Minderer, Filip Pavetic, Austin Waters, Gang Li, Ibrahim Alabdulmohsin, Lucas Beyer, Julien Amelot, Kenton Lee, Andreas Peter Steiner, Yang Li, Daniel Keysers, Anurag Arnab, Yuanzhong Xu, Keran Rong, Alexander Kolesnikov, Mojtaba Seyedhosseini, Anelia Angelova, Xiaohua Zhai, Neil Houlsby, Radu Soricut
2024	J	`jnl`	SMERF: Streamable Memory Efficient Radiance Fields for Real-Time Large-Scene Exploration. ACM Trans. Graph. Daniel Duckworth, Peter Hedman, Christian Reiser, Peter Zhizhin, Jean-François Thibert, Mario Lucic, Richard Szeliski, Jonathan T. Barron
2023	A*	`conf`	Audiovisual Masked Autoencoders. ICCV Mariana-Iuliana Georgescu, Eduardo Fonseca, Radu Tudor Ionescu, Mario Lucic, Cordelia Schmid, Anurag Arnab
2023	J	`jnl`	End-to-End Spatio-Temporal Action Localisation with Video Transformers. CoRR Alexey A. Gritsenko, Xuehan Xiong, Josip Djolonga, Mostafa Dehghani, Chen Sun, Mario Lucic, Cordelia Schmid, Anurag Arnab
2023	J	`jnl`	PaLI-X: On Scaling up a Multilingual Vision and Language Model. CoRR Xi Chen, Josip Djolonga, Piotr Padlewski, Basil Mustafa, Soravit Changpinyo, Jialin Wu, Carlos Riquelme Ruiz, Sebastian Goodman, Xiao Wang, Yi Tay, Siamak Shakeri, Mostafa Dehghani, Daniel Salz, Mario Lucic, Michael Tschannen, Arsha Nagrani, Hexiang Hu, Mandar Joshi, Bo Pang, Ceslee Montgomery, Paulina Pietrzyk, Marvin Ritter, A. J. Piergiovanni, Matthias Minderer, Filip Pavetic, Austin Waters, Gang Li, Ibrahim Alabdulmohsin, Lucas Beyer, Julien Amelot, Kenton Lee, Andreas Peter Steiner, Yang Li, Daniel Keysers, Anurag Arnab, Yuanzhong Xu, Keran Rong, Alexander Kolesnikov, Mojtaba Seyedhosseini, Anelia Angelova, Xiaohua Zhai, Neil Houlsby, Radu Soricut
2023	A*	`conf`	Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution. NeurIPS Mostafa Dehghani, Basil Mustafa, Josip Djolonga, Jonathan Heek, Matthias Minderer, Mathilde Caron, Andreas Steiner, Joan Puigcerver, Robert Geirhos, Ibrahim M. Alabdulmohsin, Avital Oliver, Piotr Padlewski, Alexey A. Gritsenko, Mario Lucic, Neil Houlsby
2023	J	`jnl`	Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution. CoRR Mostafa Dehghani, Basil Mustafa, Josip Djolonga, Jonathan Heek, Matthias Minderer, Mathilde Caron, Andreas Steiner, Joan Puigcerver, Robert Geirhos, Ibrahim Alabdulmohsin, Avital Oliver, Piotr Padlewski, Alexey A. Gritsenko, Mario Lucic, Neil Houlsby
2023	J	`jnl`	PolyViT: Co-training Vision Transformers on Images, Videos and Audio. Trans. Mach. Learn. Res. Valerii Likhosherstov, Anurag Arnab, Krzysztof Marcin Choromanski, Mario Lucic, Yi Tay, Mostafa Dehghani
2023	A*	`conf`	RUST: Latent Neural Scene Representations from Unposed Imagery. CVPR Mehdi S. M. Sajjadi, Aravindh Mahendran, Thomas Kipf, Etienne Pot, Daniel Duckworth, Mario Lucic, Klaus Greff
2023	J	`jnl`	SMERF: Streamable Memory Efficient Radiance Fields for Real-Time Large-Scene Exploration. CoRR Daniel Duckworth, Peter Hedman, Christian Reiser, Peter Zhizhin, Jean-François Thibert, Mario Lucic, Richard Szeliski, Jonathan T. Barron
2023	A*	`conf`	Scaling Vision Transformers to 22 Billion Parameters. ICML Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Peter Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, Rodolphe Jenatton, Lucas Beyer, Michael Tschannen, Anurag Arnab, Xiao Wang, Carlos Riquelme Ruiz, Matthias Minderer, Joan Puigcerver, Utku Evci, Manoj Kumar, Sjoerd van Steenkiste, Gamaleldin Fathy Elsayed, Aravindh Mahendran, Fisher Yu, Avital Oliver, Fantine Huot, Jasmijn Bastings, Mark Collier, Alexey A. Gritsenko, Vighnesh Birodkar, Cristina Nader Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetic, Dustin Tran, Thomas Kipf, Mario Lucic, Xiaohua Zhai, Daniel Keysers, Jeremiah J. Harmsen, Neil Houlsby
2023	J	`jnl`	Scaling Vision Transformers to 22 Billion Parameters. CoRR Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, Rodolphe Jenatton, Lucas Beyer, Michael Tschannen, Anurag Arnab, Xiao Wang, Carlos Riquelme, Matthias Minderer, Joan Puigcerver, Utku Evci, Manoj Kumar, Sjoerd van Steenkiste, Gamaleldin F. Elsayed, Aravindh Mahendran, Fisher Yu, Avital Oliver, Fantine Huot, Jasmijn Bastings, Mark Patrick Collier, Alexey A. Gritsenko, Vighnesh Birodkar, Cristina Nader Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetic, Dustin Tran, Thomas Kipf, Mario Lucic, Xiaohua Zhai, Daniel Keysers, Jeremiah Harmsen, Neil Houlsby
2023	A*	`conf`	Video OWL-ViT: Temporally-consistent open-world localization in video. ICCV Georg Heigold, Daniel Keysers, Matthias Minderer, Mario Lucic, Alexey A. Gritsenko, Fisher Yu, Alex Bewley, Thomas Kipf
2023	J	`jnl`	Video OWL-ViT: Temporally-consistent open-world localization in video. CoRR Georg Heigold, Matthias Minderer, Alexey A. Gritsenko, Alex Bewley, Daniel Keysers, Mario Lucic, Fisher Yu, Thomas Kipf
2022	J	`jnl`	Audiovisual Masked Autoencoders. CoRR Mariana-Iuliana Georgescu, Eduardo Fonseca, Radu Tudor Ionescu, Mario Lucic, Cordelia Schmid, Anurag Arnab
2022	J	`jnl`	Beyond Transfer Learning: Co-finetuning for Action Localisation. CoRR Anurag Arnab, Xuehan Xiong, Alexey A. Gritsenko, Rob Romijnders, Josip Djolonga, Mostafa Dehghani, Chen Sun, Mario Lucic, Cordelia Schmid
2022	A*	`conf`	Object Scene Representation Transformer. NeurIPS Mehdi S. M. Sajjadi, Daniel Duckworth, Aravindh Mahendran, Sjoerd van Steenkiste, Filip Pavetic, Mario Lucic, Leonidas J. Guibas, Klaus Greff, Thomas Kipf
2022	J	`jnl`	Object Scene Representation Transformer. CoRR Mehdi S. M. Sajjadi, Daniel Duckworth, Aravindh Mahendran, Sjoerd van Steenkiste, Filip Pavetic, Mario Lucic, Leonidas J. Guibas, Klaus Greff, Thomas Kipf
2022	J	`jnl`	RUST: Latent Neural Scene Representations from Unposed Imagery. CoRR Mehdi S. M. Sajjadi, Aravindh Mahendran, Thomas Kipf, Etienne Pot, Daniel Duckworth, Mario Lucic, Klaus Greff
2022	A*	`conf`	Scene Representation Transformer: Geometry-Free Novel View Synthesis Through Set-Latent Scene Representations. CVPR Mehdi S. M. Sajjadi, Henning Meyer, Etienne Pot, Urs Bergmann, Klaus Greff, Noha Radwan, Suhani Vora, Mario Lucic, Daniel Duckworth, Alexey Dosovitskiy, Jakob Uszkoreit, Thomas A. Funkhouser, Andrea Tagliasacchi
2022	J	`jnl`	Underspecification Presents Challenges for Credibility in Modern Machine Learning. J. Mach. Learn. Res. Alexander D'Amour, Katherine A. Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yi-An Ma, Cory Y. McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, D. Sculley
2022	A*	`conf`	VCT: A Video Compression Transformer. NeurIPS Fabian Mentzer, George Toderici, David Minnen, Sergi Caelles, Sung Jin Hwang, Mario Lucic, Eirikur Agustsson
2022	J	`jnl`	VCT: A Video Compression Transformer. CoRR Fabian Mentzer, George Toderici, David Minnen, Sung Jin Hwang, Sergi Caelles, Mario Lucic, Eirikur Agustsson
2022	A*	`conf`	Which Model to Transfer? Finding the Needle in the Growing Haystack. CVPR Cédric Renggli, André Susano Pinto, Luka Rimanic, Joan Puigcerver, Carlos Riquelme, Ce Zhang, Mario Lucic
2021	A*	`conf`	A Near-Optimal Algorithm for Debiasing Trained Machine Learning Models. NeurIPS Ibrahim M. Alabdulmohsin, Mario Lucic
2021	J	`jnl`	A Near-Optimal Algorithm for Debiasing Trained Machine Learning Models. CoRR Ibrahim M. Alabdulmohsin, Mario Lucic
2021	A*	`conf`	MLP-Mixer: An all-MLP Architecture for Vision. NeurIPS Ilya O. Tolstikhin, Neil Houlsby, Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Thomas Unterthiner, Jessica Yung, Andreas Steiner, Daniel Keysers, Jakob Uszkoreit, Mario Lucic, Alexey Dosovitskiy
2021	J	`jnl`	MLP-Mixer: An all-MLP Architecture for Vision. CoRR Ilya O. Tolstikhin, Neil Houlsby, Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Thomas Unterthiner, Jessica Yung, Andreas Steiner, Daniel Keysers, Jakob Uszkoreit, Mario Lucic, Alexey Dosovitskiy
2021	A*	`conf`	On Robustness and Transferability of Convolutional Neural Networks. CVPR Josip Djolonga, Jessica Yung, Michael Tschannen, Rob Romijnders, Lucas Beyer, Alexander Kolesnikov, Joan Puigcerver, Matthias Minderer, Alexander D'Amour, Dan Moldovan, Sylvain Gelly, Neil Houlsby, Xiaohua Zhai, Mario Lucic
2021	J	`jnl`	PolyViT: Co-training Vision Transformers on Images, Videos and Audio. CoRR Valerii Likhosherstov, Anurag Arnab, Krzysztof Choromanski, Mario Lucic, Yi Tay, Adrian Weller, Mostafa Dehghani
2021	A	`conf`	Representation learning from videos in-the-wild: An object-centric approach. WACV Rob Romijnders, Aravindh Mahendran, Michael Tschannen, Josip Djolonga, Marvin Ritter, Neil Houlsby, Mario Lucic
2021	A*	`conf`	Revisiting the Calibration of Modern Neural Networks. NeurIPS Matthias Minderer, Josip Djolonga, Rob Romijnders, Frances Hubis, Xiaohua Zhai, Neil Houlsby, Dustin Tran, Mario Lucic
2021	J	`jnl`	Revisiting the Calibration of Modern Neural Networks. CoRR Matthias Minderer, Josip Djolonga, Rob Romijnders, Frances Hubis, Xiaohua Zhai, Neil Houlsby, Dustin Tran, Mario Lucic
2021	J	`jnl`	SI-Score: An image dataset for fine-grained analysis of robustness to object location, rotation and size. CoRR Jessica Yung, Rob Romijnders, Alexander Kolesnikov, Lucas Beyer, Josip Djolonga, Neil Houlsby, Sylvain Gelly, Mario Lucic, Xiaohua Zhai
2021	J	`jnl`	Scene Representation Transformer: Geometry-Free Novel View Synthesis Through Set-Latent Scene Representations. CoRR Mehdi S. M. Sajjadi, Henning Meyer, Etienne Pot, Urs Bergmann, Klaus Greff, Noha Radwan, Suhani Vora, Mario Lucic, Daniel Duckworth, Alexey Dosovitskiy, Jakob Uszkoreit, Thomas A. Funkhouser, Andrea Tagliasacchi
2021	A*	`conf`	ViViT: A Video Vision Transformer. ICCV Anurag Arnab, Mostafa Dehghani, Georg Heigold, Chen Sun, Mario Lucic, Cordelia Schmid
2021	J	`jnl`	ViViT: A Video Vision Transformer. CoRR Anurag Arnab, Mostafa Dehghani, Georg Heigold, Chen Sun, Mario Lucic, Cordelia Schmid
2020	A*	`conf`	A Commentary on the Unsupervised Learning of Disentangled Representations. AAAI Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem
2020	J	`jnl`	A Commentary on the Unsupervised Learning of Disentangled Representations. CoRR Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem
2020	J	`jnl`	A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation. CoRR Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem
2020	J	`jnl`	A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation. J. Mach. Learn. Res. Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem
2020	A*	`conf`	On Mutual Information Maximization for Representation Learning. ICLR Michael Tschannen, Josip Djolonga, Paul K. Rubenstein, Sylvain Gelly, Mario Lucic
2020	J	`jnl`	On Robustness and Transferability of Convolutional Neural Networks. CoRR Josip Djolonga, Jessica Yung, Michael Tschannen, Rob Romijnders, Lucas Beyer, Alexander Kolesnikov, Joan Puigcerver, Matthias Minderer, Alexander D'Amour, Dan Moldovan, Sylvain Gelly, Neil Houlsby, Xiaohua Zhai, Mario Lucic
2020	A	`conf`	Precision-Recall Curves Using Information Divergence Frontiers. AISTATS Josip Djolonga, Mario Lucic, Marco Cuturi, Olivier Bachem, Olivier Bousquet, Sylvain Gelly
2020	J	`jnl`	Representation learning from videos in-the-wild: An object-centric approach. CoRR Rob Romijnders, Aravindh Mahendran, Michael Tschannen, Josip Djolonga, Marvin Ritter, Neil Houlsby, Mario Lucic
2020	A*	`conf`	Self-Supervised Learning of Video-Induced Visual Invariances. CVPR Michael Tschannen, Josip Djolonga, Marvin Ritter, Aravindh Mahendran, Neil Houlsby, Sylvain Gelly, Mario Lucic
2020	J	`jnl`	Underspecification Presents Challenges for Credibility in Modern Machine Learning. CoRR Alexander D'Amour, Katherine A. Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yi-An Ma, Cory Y. McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, D. Sculley
2020	J	`jnl`	Which Model to Transfer? Finding the Needle in the Growing Haystack. CoRR Cédric Renggli, André Susano Pinto, Luka Rimanic, Joan Puigcerver, Carlos Riquelme, Ce Zhang, Mario Lucic
2019	A*	`conf`	A Large-Scale Study on Regularization and Normalization in GANs. ICML Karol Kurach, Mario Lucic, Xiaohua Zhai, Marcin Michalski, Sylvain Gelly
2019	—	`conf`	Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations. RML@ICLR Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem
2019	A*	`conf`	Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations. ICML Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem
2019	J	`jnl`	Evaluating Generative Models Using Divergence Frontiers. CoRR Josip Djolonga, Mario Lucic, Marco Cuturi, Olivier Bachem, Olivier Bousquet, Sylvain Gelly
2019	A*	`conf`	High-Fidelity Image Generation With Fewer Labels. ICML Mario Lucic, Michael Tschannen, Marvin Ritter, Xiaohua Zhai, Olivier Bachem, Sylvain Gelly
2019	J	`jnl`	High-Fidelity Image Generation With Fewer Labels. CoRR Mario Lucic, Michael Tschannen, Marvin Ritter, Xiaohua Zhai, Olivier Bachem, Sylvain Gelly
2019	J	`jnl`	On Mutual Information Maximization for Representation Learning. CoRR Michael Tschannen, Josip Djolonga, Paul K. Rubenstein, Sylvain Gelly, Mario Lucic
2019	—	`conf`	On Self Modulation for Generative Adversarial Networks. ICLR (Poster) Ting Chen, Mario Lucic, Neil Houlsby, Sylvain Gelly
2019	A*	`conf`	Self-Supervised GANs via Auxiliary Rotation Loss. CVPR Ting Chen, Xiaohua Zhai, Marvin Ritter, Mario Lucic, Neil Houlsby
2019	J	`jnl`	Self-Supervised Learning of Video-Induced Visual Invariances. CoRR Michael Tschannen, Josip Djolonga, Marvin Ritter, Aravindh Mahendran, Neil Houlsby, Sylvain Gelly, Mario Lucic
2019	J	`jnl`	Semantic Bottleneck Scene Generation. CoRR Samaneh Azadi, Michael Tschannen, Eric Tzeng, Sylvain Gelly, Trevor Darrell, Mario Lucic
2019	J	`jnl`	The Visual Task Adaptation Benchmark. CoRR Xiaohua Zhai, Joan Puigcerver, Alexander Kolesnikov, Pierre Ruyssen, Carlos Riquelme, Mario Lucic, Josip Djolonga, André Susano Pinto, Maxim Neumann, Alexey Dosovitskiy, Lucas Beyer, Olivier Bachem, Michael Tschannen, Marcin Michalski, Olivier Bousquet, Sylvain Gelly, Neil Houlsby
2018	A*	`conf`	Are GANs Created Equal? A Large-Scale Study. NeurIPS Mario Lucic, Karol Kurach, Marcin Michalski, Sylvain Gelly, Olivier Bousquet
2018	A*	`conf`	Assessing Generative Models via Precision and Recall. NeurIPS Mehdi S. M. Sajjadi, Olivier Bachem, Mario Lucic, Olivier Bousquet, Sylvain Gelly
2018	J	`jnl`	Assessing Generative Models via Precision and Recall. CoRR Mehdi S. M. Sajjadi, Olivier Bachem, Mario Lucic, Olivier Bousquet, Sylvain Gelly
2018	J	`jnl`	Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations. CoRR Francesco Locatello, Stefan Bauer, Mario Lucic, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem
2018	A*	`conf`	Deep Generative Models for Distribution-Preserving Lossy Compression. NeurIPS Michael Tschannen, Eirikur Agustsson, Mario Lucic
2018	J	`jnl`	Deep Generative Models for Distribution-Preserving Lossy Compression. CoRR Michael Tschannen, Eirikur Agustsson, Mario Lucic
2018	J	`jnl`	On Self Modulation for Generative Adversarial Networks. CoRR Ting Chen, Mario Lucic, Neil Houlsby, Sylvain Gelly
2018	A	`conf`	One-shot Coresets: The Case of k-Clustering. AISTATS Olivier Bachem, Mario Lucic, Silvio Lattanzi
2018	J	`jnl`	Recent Advances in Autoencoder-Based Representation Learning. CoRR Michael Tschannen, Olivier Bachem, Mario Lucic
2018	A*	`conf`	Scalable k -Means Clustering via Lightweight Coresets. KDD Olivier Bachem, Mario Lucic, Andreas Krause
2018	J	`jnl`	Self-Supervised Generative Adversarial Networks. CoRR Ting Chen, Xiaohua Zhai, Marvin Ritter, Mario Lucic, Neil Houlsby
2018	J	`jnl`	The GAN Landscape: Losses, Architectures, Regularization, and Normalization. CoRR Karol Kurach, Mario Lucic, Xiaohua Zhai, Marcin Michalski, Sylvain Gelly
2017	J	`jnl`	Are GANs Created Equal? A Large-Scale Study. CoRR Mario Lucic, Karol Kurach, Marcin Michalski, Sylvain Gelly, Olivier Bousquet
2017	—	`—`	Computational and Statistical Tradeoffs via Data Summarization. Mario Lucic
2017	A*	`conf`	Distributed and Provably Good Seedings for k-Means in Constant Rounds. ICML Olivier Bachem, Mario Lucic, Andreas Krause
2017	J	`jnl`	One-Shot Coresets: The Case of k-Clustering. CoRR Olivier Bachem, Mario Lucic, Silvio Lattanzi
2017	J	`jnl`	Scalable and Distributed Clustering via Lightweight Coresets. CoRR Olivier Bachem, Mario Lucic, Andreas Krause
2017	—	`conf`	Stochastic Submodular Maximization: The Case of Coverage Functions. NIPS Mohammad Reza Karimi, Mario Lucic, S. Hamed Hassani, Andreas Krause
2017	J	`jnl`	Stochastic Submodular Maximization: The Case of Coverage Functions. CoRR Mohammad Reza Karimi, Mario Lucic, S. Hamed Hassani, Andreas Krause
2017	J	`jnl`	Training Gaussian Mixture Models at Scale via Coresets. J. Mach. Learn. Res. Mario Lucic, Matthew Faulkner, Andreas Krause, Dan Feldman
2017	J	`jnl`	Uniform Deviation Bounds for Unbounded Loss Functions like k-Means. CoRR Olivier Bachem, Mario Lucic, S. Hamed Hassani, Andreas Krause
2017	A*	`conf`	Uniform Deviation Bounds for k-Means Clustering. ICML Olivier Bachem, Mario Lucic, S. Hamed Hassani, Andreas Krause
2016	A*	`conf`	Approximate K-Means++ in Sublinear Time. AAAI Olivier Bachem, Mario Lucic, S. Hamed Hassani, Andreas Krause
2016	—	`conf`	Fast and Provably Good Seedings for k-Means. NIPS Olivier Bachem, Mario Lucic, Seyed Hamed Hassani, Andreas Krause
2016	A*	`conf`	Horizontally Scalable Submodular Maximization. ICML Mario Lucic, Olivier Bachem, Morteza Zadimoghaddam, Andreas Krause
2016	J	`jnl`	Horizontally Scalable Submodular Maximization. CoRR Mario Lucic, Olivier Bachem, Morteza Zadimoghaddam, Andreas Krause
2016	A*	`conf`	Linear-Time Outlier Detection via Sensitivity. IJCAI Mario Lucic, Olivier Bachem, Andreas Krause
2016	J	`jnl`	Linear-time Outlier Detection via Sensitivity. CoRR Mario Lucic, Olivier Bachem, Andreas Krause
2016	—	`conf`	Quantifying Location Privacy Leakage from Transaction Prices. ESORICS (2) Arthur Gervais, Hubert Ritzdorf, Mario Lucic, Vincent Lenders, Srdjan Capkun
2016	A	`conf`	Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures. AISTATS Mario Lucic, Olivier Bachem, Andreas Krause
2016	J	`jnl`	Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning. CoRR Mario Lucic, Mesrob I. Ohannessian, Amin Karbasi, Andreas Krause
2015	A*	`conf`	Coresets for Nonparametric Estimation - the Case of DP-Means. ICML Olivier Bachem, Mario Lucic, Andreas Krause
2015	J	`jnl`	Quantifying Location Privacy Leakage from Transaction Prices. IACR Cryptol. ePrint Arch. Arthur Gervais, Hubert Ritzdorf, Mario Lucic, Srdjan Capkun
2015	J	`jnl`	Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures. CoRR Mario Lucic, Olivier Bachem, Andreas Krause
2015	A	`conf`	Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning. AISTATS Mario Lucic, Mesrob I. Ohannessian, Amin Karbasi, Andreas Krause
2014	—	`conf`	Fast and Robust Least Squares Estimation in Corrupted Linear Models. NIPS Brian McWilliams, Gabriel Krummenacher, Mario Lucic, Joachim M. Buhmann