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2020 – today
- 2024
[j5]Daniel Duckworth
, Peter Hedman, Christian Reiser, Peter Zhizhin, Jean-François Thibert, Mario Lucic, Richard Szeliski, Jonathan T. Barron:
SMERF: Streamable Memory Efficient Radiance Fields for Real-Time Large-Scene Exploration. ACM Trans. Graph. 43(4): 63:1-63:13 (2024)- [c44]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:
On Scaling Up a Multilingual Vision and Language Model. CVPR 2024: 14432-14444 - [c43]Alexey A. Gritsenko, Xuehan Xiong, Josip Djolonga, Mostafa Dehghani, Chen Sun, Mario Lucic, Cordelia Schmid, Anurag Arnab:
End-to-End Spatio-Temporal Action Localisation with Video Transformers. CVPR 2024: 18373-18383 - 2023
- [j4]Valerii Likhosherstov, Anurag Arnab, Krzysztof Marcin Choromanski, Mario Lucic, Yi Tay, Mostafa Dehghani:
PolyViT: Co-training Vision Transformers on Images, Videos and Audio. Trans. Mach. Learn. Res. 2023 (2023) - [c42]Mehdi S. M. Sajjadi, Aravindh Mahendran, Thomas Kipf, Etienne Pot, Daniel Duckworth, Mario Lucic, Klaus Greff:
RUST: Latent Neural Scene Representations from Unposed Imagery. CVPR 2023: 17297-17306 - [c41]Georg Heigold, Daniel Keysers, Matthias Minderer, Mario Lucic, Alexey A. Gritsenko, Fisher Yu, Alex Bewley, Thomas Kipf:
Video OWL-ViT: Temporally-consistent open-world localization in video. ICCV 2023: 13756-13765 - [c40]Mariana-Iuliana Georgescu, Eduardo Fonseca, Radu Tudor Ionescu, Mario Lucic, Cordelia Schmid, Anurag Arnab:
Audiovisual Masked Autoencoders. ICCV 2023: 16098-16108 - [c39]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:
Scaling Vision Transformers to 22 Billion Parameters. ICML 2023: 7480-7512 - [c38]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:
Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution. NeurIPS 2023 - [i47]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:
Scaling Vision Transformers to 22 Billion Parameters. CoRR abs/2302.05442 (2023) - [i46]Alexey A. Gritsenko, Xuehan Xiong, Josip Djolonga, Mostafa Dehghani, Chen Sun, Mario Lucic, Cordelia Schmid, Anurag Arnab:
End-to-End Spatio-Temporal Action Localisation with Video Transformers. CoRR abs/2304.12160 (2023) - [i45]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:
PaLI-X: On Scaling up a Multilingual Vision and Language Model. CoRR abs/2305.18565 (2023) - [i44]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:
Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution. CoRR abs/2307.06304 (2023) - [i43]Georg Heigold, Matthias Minderer, Alexey A. Gritsenko, Alex Bewley, Daniel Keysers, Mario Lucic, Fisher Yu, Thomas Kipf:
Video OWL-ViT: Temporally-consistent open-world localization in video. CoRR abs/2308.11093 (2023) - [i42]Daniel Duckworth, Peter Hedman, Christian Reiser, Peter Zhizhin, Jean-François Thibert, Mario Lucic, Richard Szeliski, Jonathan T. Barron:
SMERF: Streamable Memory Efficient Radiance Fields for Real-Time Large-Scene Exploration. CoRR abs/2312.07541 (2023) - 2022
- [j3]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:
Underspecification Presents Challenges for Credibility in Modern Machine Learning. J. Mach. Learn. Res. 23: 226:1-226:61 (2022) - [c37]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:
Scene Representation Transformer: Geometry-Free Novel View Synthesis Through Set-Latent Scene Representations. CVPR 2022: 6219-6228 - [c36]Cédric Renggli, André Susano Pinto, Luka Rimanic, Joan Puigcerver, Carlos Riquelme, Ce Zhang, Mario Lucic:
Which Model to Transfer? Finding the Needle in the Growing Haystack. CVPR 2022: 9195-9204 - [c35]Fabian Mentzer, George Toderici, David Minnen, Sergi Caelles, Sung Jin Hwang, Mario Lucic, Eirikur Agustsson:
VCT: A Video Compression Transformer. NeurIPS 2022 - [c34]Mehdi S. M. Sajjadi, Daniel Duckworth, Aravindh Mahendran, Sjoerd van Steenkiste, Filip Pavetic, Mario Lucic, Leonidas J. Guibas, Klaus Greff, Thomas Kipf:
Object Scene Representation Transformer. NeurIPS 2022 - [i41]Mehdi S. M. Sajjadi, Daniel Duckworth, Aravindh Mahendran, Sjoerd van Steenkiste, Filip Pavetic, Mario Lucic, Leonidas J. Guibas, Klaus Greff, Thomas Kipf:
Object Scene Representation Transformer. CoRR abs/2206.06922 (2022) - [i40]Fabian Mentzer, George Toderici, David Minnen, Sung Jin Hwang, Sergi Caelles, Mario Lucic, Eirikur Agustsson:
VCT: A Video Compression Transformer. CoRR abs/2206.07307 (2022) - [i39]Anurag Arnab, Xuehan Xiong, Alexey A. Gritsenko, Rob Romijnders, Josip Djolonga, Mostafa Dehghani, Chen Sun, Mario Lucic, Cordelia Schmid:
Beyond Transfer Learning: Co-finetuning for Action Localisation. CoRR abs/2207.03807 (2022) - [i38]Mehdi S. M. Sajjadi, Aravindh Mahendran, Thomas Kipf, Etienne Pot, Daniel Duckworth, Mario Lucic, Klaus Greff:
RUST: Latent Neural Scene Representations from Unposed Imagery. CoRR abs/2211.14306 (2022) - [i37]Mariana-Iuliana Georgescu, Eduardo Fonseca, Radu Tudor Ionescu, Mario Lucic, Cordelia Schmid, Anurag Arnab:
Audiovisual Masked Autoencoders. CoRR abs/2212.05922 (2022) - 2021
- [c33]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:
On Robustness and Transferability of Convolutional Neural Networks. CVPR 2021: 16458-16468 - [c32]Anurag Arnab, Mostafa Dehghani, Georg Heigold, Chen Sun, Mario Lucic, Cordelia Schmid:
ViViT: A Video Vision Transformer. ICCV 2021: 6816-6826 - [c31]Ibrahim M. Alabdulmohsin, Mario Lucic:
A Near-Optimal Algorithm for Debiasing Trained Machine Learning Models. NeurIPS 2021: 8072-8084 - [c30]Matthias Minderer, Josip Djolonga, Rob Romijnders, Frances Hubis, Xiaohua Zhai, Neil Houlsby, Dustin Tran, Mario Lucic:
Revisiting the Calibration of Modern Neural Networks. NeurIPS 2021: 15682-15694 - [c29]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:
MLP-Mixer: An all-MLP Architecture for Vision. NeurIPS 2021: 24261-24272 - [c28]Rob Romijnders, Aravindh Mahendran, Michael Tschannen, Josip Djolonga, Marvin Ritter, Neil Houlsby, Mario Lucic:
Representation learning from videos in-the-wild: An object-centric approach. WACV 2021: 177-187 - [i36]Anurag Arnab, Mostafa Dehghani, Georg Heigold, Chen Sun, Mario Lucic, Cordelia Schmid:
ViViT: A Video Vision Transformer. CoRR abs/2103.15691 (2021) - [i35]Jessica Yung, Rob Romijnders, Alexander Kolesnikov, Lucas Beyer, Josip Djolonga, Neil Houlsby, Sylvain Gelly, Mario Lucic, Xiaohua Zhai:
SI-Score: An image dataset for fine-grained analysis of robustness to object location, rotation and size. CoRR abs/2104.04191 (2021) - [i34]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:
MLP-Mixer: An all-MLP Architecture for Vision. CoRR abs/2105.01601 (2021) - [i33]Matthias Minderer, Josip Djolonga, Rob Romijnders, Frances Hubis, Xiaohua Zhai, Neil Houlsby, Dustin Tran, Mario Lucic:
Revisiting the Calibration of Modern Neural Networks. CoRR abs/2106.07998 (2021) - [i32]Ibrahim M. Alabdulmohsin, Mario Lucic:
A Near-Optimal Algorithm for Debiasing Trained Machine Learning Models. CoRR abs/2106.12887 (2021) - [i31]Valerii Likhosherstov, Anurag Arnab, Krzysztof Choromanski, Mario Lucic, Yi Tay, Adrian Weller, Mostafa Dehghani:
PolyViT: Co-training Vision Transformers on Images, Videos and Audio. CoRR abs/2111.12993 (2021) - [i30]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:
Scene Representation Transformer: Geometry-Free Novel View Synthesis Through Set-Latent Scene Representations. CoRR abs/2111.13152 (2021) - 2020
- [j2]Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem:
A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation. J. Mach. Learn. Res. 21: 209:1-209:62 (2020) - [c27]Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem:
A Commentary on the Unsupervised Learning of Disentangled Representations. AAAI 2020: 13681-13684 - [c26]Josip Djolonga, Mario Lucic, Marco Cuturi, Olivier Bachem, Olivier Bousquet, Sylvain Gelly:
Precision-Recall Curves Using Information Divergence Frontiers. AISTATS 2020: 2550-2559 - [c25]Michael Tschannen, Josip Djolonga, Marvin Ritter, Aravindh Mahendran, Neil Houlsby, Sylvain Gelly, Mario Lucic:
Self-Supervised Learning of Video-Induced Visual Invariances. CVPR 2020: 13803-13812 - [c24]Michael Tschannen, Josip Djolonga, Paul K. Rubenstein, Sylvain Gelly, Mario Lucic:
On Mutual Information Maximization for Representation Learning. ICLR 2020 - [i29]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:
On Robustness and Transferability of Convolutional Neural Networks. CoRR abs/2007.08558 (2020) - [i28]Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem:
A Commentary on the Unsupervised Learning of Disentangled Representations. CoRR abs/2007.14184 (2020) - [i27]Rob Romijnders, Aravindh Mahendran, Michael Tschannen, Josip Djolonga, Marvin Ritter, Neil Houlsby, Mario Lucic:
Representation learning from videos in-the-wild: An object-centric approach. CoRR abs/2010.02808 (2020) - [i26]Cédric Renggli, André Susano Pinto, Luka Rimanic, Joan Puigcerver, Carlos Riquelme, Ce Zhang, Mario Lucic:
Which Model to Transfer? Finding the Needle in the Growing Haystack. CoRR abs/2010.06402 (2020) - [i25]Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem:
A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation. CoRR abs/2010.14766 (2020) - [i24]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:
Underspecification Presents Challenges for Credibility in Modern Machine Learning. CoRR abs/2011.03395 (2020)
2010 – 2019
- 2019
- [c23]Ting Chen, Xiaohua Zhai, Marvin Ritter, Mario Lucic, Neil Houlsby:
Self-Supervised GANs via Auxiliary Rotation Loss. CVPR 2019: 12154-12163 - [c22]Ting Chen, Mario Lucic, Neil Houlsby, Sylvain Gelly:
On Self Modulation for Generative Adversarial Networks. ICLR (Poster) 2019 - [c21]Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem:
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations. RML@ICLR 2019 - [c20]Karol Kurach, Mario Lucic, Xiaohua Zhai, Marcin Michalski, Sylvain Gelly:
A Large-Scale Study on Regularization and Normalization in GANs. ICML 2019: 3581-3590 - [c19]Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem:
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations. ICML 2019: 4114-4124 - [c18]Mario Lucic, Michael Tschannen, Marvin Ritter, Xiaohua Zhai, Olivier Bachem, Sylvain Gelly:
High-Fidelity Image Generation With Fewer Labels. ICML 2019: 4183-4192 - [i23]Mario Lucic, Michael Tschannen, Marvin Ritter, Xiaohua Zhai, Olivier Bachem, Sylvain Gelly:
High-Fidelity Image Generation With Fewer Labels. CoRR abs/1903.02271 (2019) - [i22]Josip Djolonga, Mario Lucic, Marco Cuturi, Olivier Bachem, Olivier Bousquet, Sylvain Gelly:
Evaluating Generative Models Using Divergence Frontiers. CoRR abs/1905.10768 (2019) - [i21]Michael Tschannen, Josip Djolonga, Paul K. Rubenstein, Sylvain Gelly, Mario Lucic:
On Mutual Information Maximization for Representation Learning. CoRR abs/1907.13625 (2019) - [i20]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:
The Visual Task Adaptation Benchmark. CoRR abs/1910.04867 (2019) - [i19]Samaneh Azadi, Michael Tschannen, Eric Tzeng, Sylvain Gelly, Trevor Darrell, Mario Lucic:
Semantic Bottleneck Scene Generation. CoRR abs/1911.11357 (2019) - [i18]Michael Tschannen, Josip Djolonga, Marvin Ritter, Aravindh Mahendran, Neil Houlsby, Sylvain Gelly, Mario Lucic:
Self-Supervised Learning of Video-Induced Visual Invariances. CoRR abs/1912.02783 (2019) - 2018
- [c17]Olivier Bachem, Mario Lucic, Silvio Lattanzi:
One-shot Coresets: The Case of k-Clustering. AISTATS 2018: 784-792 - [c16]Olivier Bachem, Mario Lucic, Andreas Krause:
Scalable k -Means Clustering via Lightweight Coresets. KDD 2018: 1119-1127 - [c15]Mario Lucic, Karol Kurach, Marcin Michalski, Sylvain Gelly, Olivier Bousquet:
Are GANs Created Equal? A Large-Scale Study. NeurIPS 2018: 698-707 - [c14]Mehdi S. M. Sajjadi, Olivier Bachem, Mario Lucic, Olivier Bousquet, Sylvain Gelly:
Assessing Generative Models via Precision and Recall. NeurIPS 2018: 5234-5243 - [c13]Michael Tschannen, Eirikur Agustsson, Mario Lucic:
Deep Generative Models for Distribution-Preserving Lossy Compression. NeurIPS 2018: 5933-5944 - [i17]Michael Tschannen, Eirikur Agustsson, Mario Lucic:
Deep Generative Models for Distribution-Preserving Lossy Compression. CoRR abs/1805.11057 (2018) - [i16]Mehdi S. M. Sajjadi, Olivier Bachem, Mario Lucic, Olivier Bousquet, Sylvain Gelly:
Assessing Generative Models via Precision and Recall. CoRR abs/1806.00035 (2018) - [i15]Karol Kurach, Mario Lucic, Xiaohua Zhai, Marcin Michalski, Sylvain Gelly:
The GAN Landscape: Losses, Architectures, Regularization, and Normalization. CoRR abs/1807.04720 (2018) - [i14]Ting Chen, Mario Lucic, Neil Houlsby, Sylvain Gelly:
On Self Modulation for Generative Adversarial Networks. CoRR abs/1810.01365 (2018) - [i13]Ting Chen, Xiaohua Zhai, Marvin Ritter, Mario Lucic, Neil Houlsby:
Self-Supervised Generative Adversarial Networks. CoRR abs/1811.11212 (2018) - [i12]Francesco Locatello, Stefan Bauer, Mario Lucic, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem:
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations. CoRR abs/1811.12359 (2018) - [i11]Michael Tschannen, Olivier Bachem, Mario Lucic:
Recent Advances in Autoencoder-Based Representation Learning. CoRR abs/1812.05069 (2018) - 2017
- [b1]Mario Lucic:
Computational and Statistical Tradeoffs via Data Summarization. ETH Zurich, Zürich, Switzerland, 2017 - [j1]Mario Lucic, Matthew Faulkner, Andreas Krause, Dan Feldman:
Training Gaussian Mixture Models at Scale via Coresets. J. Mach. Learn. Res. 18: 160:1-160:25 (2017) - [c12]Olivier Bachem, Mario Lucic, S. Hamed Hassani, Andreas Krause:
Uniform Deviation Bounds for k-Means Clustering. ICML 2017: 283-291 - [c11]Olivier Bachem, Mario Lucic, Andreas Krause:
Distributed and Provably Good Seedings for k-Means in Constant Rounds. ICML 2017: 292-300 - [c10]Mohammad Reza Karimi, Mario Lucic, S. Hamed Hassani, Andreas Krause:
Stochastic Submodular Maximization: The Case of Coverage Functions. NIPS 2017: 6853-6863 - [i10]Olivier Bachem, Mario Lucic, Andreas Krause:
Scalable and Distributed Clustering via Lightweight Coresets. CoRR abs/1702.08248 (2017) - [i9]Olivier Bachem, Mario Lucic, S. Hamed Hassani, Andreas Krause:
Uniform Deviation Bounds for Unbounded Loss Functions like k-Means. CoRR abs/1702.08249 (2017) - [i8]Mohammad Reza Karimi, Mario Lucic, S. Hamed Hassani, Andreas Krause:
Stochastic Submodular Maximization: The Case of Coverage Functions. CoRR abs/1711.01566 (2017) - [i7]Olivier Bachem, Mario Lucic, Silvio Lattanzi:
One-Shot Coresets: The Case of k-Clustering. CoRR abs/1711.09649 (2017) - [i6]Mario Lucic, Karol Kurach, Marcin Michalski, Sylvain Gelly, Olivier Bousquet:
Are GANs Created Equal? A Large-Scale Study. CoRR abs/1711.10337 (2017) - 2016
- [c9]Olivier Bachem, Mario Lucic, S. Hamed Hassani, Andreas Krause:
Approximate K-Means++ in Sublinear Time. AAAI 2016: 1459-1467 - [c8]Mario Lucic, Olivier Bachem, Andreas Krause:
Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures. AISTATS 2016: 1-9 - [c7]Arthur Gervais, Hubert Ritzdorf, Mario Lucic, Vincent Lenders, Srdjan Capkun:
Quantifying Location Privacy Leakage from Transaction Prices. ESORICS (2) 2016: 382-405 - [c6]Mario Lucic, Olivier Bachem, Morteza Zadimoghaddam, Andreas Krause:
Horizontally Scalable Submodular Maximization. ICML 2016: 2981-2989 - [c5]Mario Lucic, Olivier Bachem, Andreas Krause:
Linear-Time Outlier Detection via Sensitivity. IJCAI 2016: 1795-1801 - [c4]Olivier Bachem, Mario Lucic, Seyed Hamed Hassani, Andreas Krause:
Fast and Provably Good Seedings for k-Means. NIPS 2016: 55-63 - [i5]Mario Lucic, Olivier Bachem, Andreas Krause:
Linear-time Outlier Detection via Sensitivity. CoRR abs/1605.00519 (2016) - [i4]Mario Lucic, Mesrob I. Ohannessian, Amin Karbasi, Andreas Krause:
Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning. CoRR abs/1605.00529 (2016) - [i3]Mario Lucic, Olivier Bachem, Morteza Zadimoghaddam, Andreas Krause:
Horizontally Scalable Submodular Maximization. CoRR abs/1605.09619 (2016) - 2015
- [c3]Mario Lucic, Mesrob I. Ohannessian, Amin Karbasi, Andreas Krause:
Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning. AISTATS 2015 - [c2]Olivier Bachem, Mario Lucic, Andreas Krause:
Coresets for Nonparametric Estimation - the Case of DP-Means. ICML 2015: 209-217 - [i2]Mario Lucic, Olivier Bachem, Andreas Krause:
Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures. CoRR abs/1508.05243 (2015) - [i1]Arthur Gervais, Hubert Ritzdorf, Mario Lucic, Srdjan Capkun:
Quantifying Location Privacy Leakage from Transaction Prices. IACR Cryptol. ePrint Arch. 2015: 496 (2015) - 2014
- [c1]Brian McWilliams, Gabriel Krummenacher, Mario Lucic, Joachim M. Buhmann:
Fast and Robust Least Squares Estimation in Corrupted Linear Models. NIPS 2014: 415-423
Coauthor Index
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Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-31 21:10 CET by the dblp team
all metadata released as open data under CC0 1.0 license
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since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
