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ORCIDIbrahim Alabdulmohsin
Person information
- affiliation: Google Research, Zurich, Switzerland
- affiliation (former): King Abdullah University of Science & Technology, Computer, Electrical and Mathematical Sciences & Engineering Division, Thuwal, Saudi Arabia
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2020 – today
- 2023
[c20]Ibrahim Alabdulmohsin, Nicole Chiou, Alexander D'Amour, Arthur Gretton, Sanmi Koyejo, Matt J. Kusner, Stephen R. Pfohl, Olawale Salaudeen, Jessica Schrouff, Katherine Tsai:
Adapting to Latent Subgroup Shifts via Concepts and Proxies. AISTATS 2023: 9637-9661- [c19]Lucas Beyer, Pavel Izmailov, Alexander Kolesnikov, Mathilde Caron, Simon Kornblith, Xiaohua Zhai, Matthias Minderer, Michael Tschannen, Ibrahim Alabdulmohsin, Filip Pavetic:
FlexiViT: One Model for All Patch Sizes. CVPR 2023: 14496-14506 - [c18]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 - [i19]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 N. 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) - [i18]Ibrahim Alabdulmohsin, Xiaohua Zhai, Alexander Kolesnikov, Lucas Beyer:
Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design. CoRR abs/2305.13035 (2023) - [i17]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) - [i16]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) - 2022
- [c17]Ibrahim M. Alabdulmohsin, Behnam Neyshabur, Xiaohua Zhai:
Revisiting Neural Scaling Laws in Language and Vision. NeurIPS 2022 - [c16]Ibrahim M. Alabdulmohsin, Jessica Schrouff, Sanmi Koyejo:
A Reduction to Binary Approach for Debiasing Multiclass Datasets. NeurIPS 2022 - [c15]Jessica Schrouff, Natalie Harris, Sanmi Koyejo, Ibrahim M. Alabdulmohsin, Eva Schnider, Krista Opsahl-Ong, Alexander Brown, Subhrajit Roy, Diana Mincu, Christina Chen, Awa Dieng, Yuan Liu, Vivek Natarajan, Alan Karthikesalingam, Katherine A. Heller, Silvia Chiappa, Alexander D'Amour:
Diagnosing failures of fairness transfer across distribution shift in real-world medical settings. NeurIPS 2022 - [c14]Alexander Soen, Ibrahim M. Alabdulmohsin, Sanmi Koyejo, Yishay Mansour, Nyalleng Moorosi, Richard Nock, Ke Sun, Lexing Xie:
Fair Wrapping for Black-box Predictions. NeurIPS 2022 - [i15]Alexander Soen, Ibrahim Alabdulmohsin, Sanmi Koyejo, Yishay Mansour, Nyalleng Moorosi, Richard Nock, Ke Sun, Lexing Xie:
Fair Wrapping for Black-box Predictions. CoRR abs/2201.12947 (2022) - [i14]Jessica Schrouff, Natalie Harris, Oluwasanmi Koyejo, Ibrahim Alabdulmohsin, Eva Schnider, Krista Opsahl-Ong, Alexander Brown, Subhrajit Roy, Diana Mincu, Christina Chen, Awa Dieng, Yuan Liu, Vivek Natarajan, Alan Karthikesalingam, Katherine A. Heller, Silvia Chiappa, Alexander D'Amour:
Maintaining fairness across distribution shift: do we have viable solutions for real-world applications? CoRR abs/2202.01034 (2022) - [i13]Ibrahim Alabdulmohsin, Jessica Schrouff, Oluwasanmi Koyejo:
A Reduction to Binary Approach for Debiasing Multiclass Datasets. CoRR abs/2205.15860 (2022) - [i12]Ibrahim Alabdulmohsin, Behnam Neyshabur, Xiaohua Zhai:
Revisiting Neural Scaling Laws in Language and Vision. CoRR abs/2209.06640 (2022) - [i11]Amr Khalifa, Michael C. Mozer, Hanie Sedghi, Behnam Neyshabur, Ibrahim Alabdulmohsin:
Layer-Stack Temperature Scaling. CoRR abs/2211.10193 (2022) - [i10]Lucas Beyer, Pavel Izmailov, Alexander Kolesnikov, Mathilde Caron, Simon Kornblith, Xiaohua Zhai, Matthias Minderer, Michael Tschannen, Ibrahim Alabdulmohsin, Filip Pavetic:
FlexiViT: One Model for All Patch Sizes. CoRR abs/2212.08013 (2022) - [i9]Ibrahim Alabdulmohsin, Nicole Chiou, Alexander D'Amour, Arthur Gretton, Sanmi Koyejo, Matt J. Kusner, Stephen R. Pfohl, Olawale Salaudeen, Jessica Schrouff, Katherine Tsai:
Adapting to Latent Subgroup Shifts via Concepts and Proxies. CoRR abs/2212.11254 (2022) - 2021
- [c13]Ibrahim M. Alabdulmohsin, Mario Lucic:
A Near-Optimal Algorithm for Debiasing Trained Machine Learning Models. NeurIPS 2021: 8072-8084 - [i8]Ibrahim M. Alabdulmohsin:
A Generalization of Classical Formulas in Numerical Integration and Series Convergence Acceleration. CoRR abs/2106.07621 (2021) - [i7]Ibrahim M. Alabdulmohsin, Mario Lucic:
A Near-Optimal Algorithm for Debiasing Trained Machine Learning Models. CoRR abs/2106.12887 (2021) - [i6]Ibrahim M. Alabdulmohsin, Larisa Markeeva, Daniel Keysers, Ilya O. Tolstikhin:
A Generalized Lottery Ticket Hypothesis. CoRR abs/2107.06825 (2021) - [i5]Ibrahim M. Alabdulmohsin, Hartmut Maennel, Daniel Keysers:
The Impact of Reinitialization on Generalization in Convolutional Neural Networks. CoRR abs/2109.00267 (2021) - 2020
- [j2]Ibrahim M. Alabdulmohsin:
Towards a Unified Theory of Learning and Information. Entropy 22(4): 438 (2020) - [c12]Hartmut Maennel, Ibrahim M. Alabdulmohsin, Ilya O. Tolstikhin, Robert J. N. Baldock, Olivier Bousquet, Sylvain Gelly, Daniel Keysers:
What Do Neural Networks Learn When Trained With Random Labels? NeurIPS 2020 - [i4]Ibrahim M. Alabdulmohsin:
Fair Classification via Unconstrained Optimization. CoRR abs/2005.14621 (2020) - [i3]Hartmut Maennel, Ibrahim M. Alabdulmohsin, Ilya O. Tolstikhin, Robert J. N. Baldock, Olivier Bousquet, Sylvain Gelly, Daniel Keysers:
What Do Neural Networks Learn When Trained With Random Labels? CoRR abs/2006.10455 (2020)
2010 – 2019
- 2018
- [c11]Ibrahim M. Alabdulmohsin:
Information Theoretic Guarantees for Empirical Risk Minimization with Applications to Model Selection and Large-Scale Optimization. ICML 2018: 149-158 - [c10]Ibrahim M. Alabdulmohsin:
Axiomatic Characterization of AdaBoost and the Multiplicative Weight Update Procedure. ECML/PKDD (1) 2018: 591-604 - 2017
- [b1]Ibrahim Alabdulmohsin:
Learning via Query Synthesis. King Abdullah University of Science and Technology, Thuwal, Saudi Arabia, 2017 - [c9]Ibrahim M. Alabdulmohsin:
An Information-Theoretic Route from Generalization in Expectation to Generalization in Probability. AISTATS 2017: 92-100 - 2016
- [j1]Ibrahim M. Alabdulmohsin
, Moustapha Cissé, Xin Gao, Xiangliang Zhang:
Large margin classification with indefinite similarities. Mach. Learn. 103(2): 215-237 (2016) - [c8]Ibrahim M. Alabdulmohsin, Yufei Han, Yun Shen, Xiangliang Zhang:
Content-Agnostic Malware Detection in Heterogeneous Malicious Distribution Graph. CIKM 2016: 2395-2400 - [c7]Ibrahim M. Alabdulmohsin, Moustapha Cissé, Xiangliang Zhang:
Is Attribute-Based Zero-Shot Learning an Ill-Posed Strategy? ECML/PKDD (1) 2016: 749-760 - [i2]Ibrahim M. Alabdulmohsin:
Uniform Generalization, Concentration, and Adaptive Learning. CoRR abs/1608.06072 (2016) - 2015
- [c6]Ibrahim M. Alabdulmohsin, Xin Gao, Xiangliang Zhang:
Efficient Active Learning of Halfspaces via Query Synthesis. AAAI 2015: 2483-2489 - [c5]Ibrahim M. Alabdulmohsin:
Algorithmic Stability and Uniform Generalization. NIPS 2015: 19-27 - 2014
- [c4]Ibrahim M. Alabdulmohsin, Xin Gao, Xiangliang Zhang:
Support vector machines with indefinite kernels. ACML 2014 - [c3]Ibrahim M. Alabdulmohsin, Xin Gao, Xiangliang Zhang:
Adding Robustness to Support Vector Machines Against Adversarial Reverse Engineering. CIKM 2014: 231-240 - [c2]Ibrahim M. Alabdulmohsin:
Interference in wireless ad hoc networks with smart antennas. IWCMC 2014: 666-671 - [c1]Ibrahim M. Alabdulmohsin, Amal Hyadi, Laila H. Afify, Basem Shihada:
End-to-end delay analysis in wireless sensor networks with service vacation. WCNC 2014: 2799-2804 - [i1]Ibrahim M. Alabdulmohsin:
A Mathematical Theory of Learning. CoRR abs/1405.1513 (2014)
Coauthor Index
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last updated on 2023-09-19 23:25 CEST by the dblp team
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