Ibrahim Alabdulmohsin

According to our database, Ibrahim Alabdulmohsin authored at least 39 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

LocCa: Visual Pretraining with Location-aware Captioners.

Bo Wan, Michael Tschannen, Yongqin Xian, Filip Pavetic, Ibrahim Alabdulmohsin, Xiao Wang, André Susano Pinto, Andreas Steiner, Lucas Beyer, Xiaohua Zhai

CoRR, 2024

CLIP the Bias: How Useful is Balancing Data in Multimodal Learning?

Ibrahim Alabdulmohsin, Xiao Wang, Andreas Steiner, Priya Goyal, Alexander D'Amour, Xiaohua Zhai

CoRR, 2024

Fractal Patterns May Unravel the Intelligence in Next-Token Prediction.

Ibrahim Alabdulmohsin, Vinh Q. Tran, Mostafa Dehghani

CoRR, 2024

2023

PaLI-3 Vision Language Models: Smaller, Faster, Stronger.

Xi Chen, Xiao Wang, Lucas Beyer, Alexander Kolesnikov, Jialin Wu, Paul Voigtlaender, Basil Mustafa, Sebastian Goodman, Ibrahim Alabdulmohsin, Piotr Padlewski, Daniel Salz, Xi Xiong, Daniel Vlasic, Filip Pavetic, Keran Rong, Tianli Yu, Daniel Keysers, Xiaohua Zhai, Radu Soricut

CoRR, 2023

PaLI-X: On Scaling up a Multilingual Vision and Language Model.

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

CoRR, 2023

Scaling Vision Transformers to 22 Billion Parameters.

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

CoRR, 2023

Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design.

Ibrahim M. Alabdulmohsin, Xiaohua Zhai, Alexander Kolesnikov, Lucas Beyer

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution.

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Scaling Vision Transformers to 22 Billion Parameters.

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

Proceedings of the International Conference on Machine Learning, 2023

FlexiViT: One Model for All Patch Sizes.

Lucas Beyer, Pavel Izmailov, Alexander Kolesnikov, Mathilde Caron, Simon Kornblith, Xiaohua Zhai, Matthias Minderer, Michael Tschannen, Ibrahim Alabdulmohsin, Filip Pavetic

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Adapting to Latent Subgroup Shifts via Concepts and Proxies.

Ibrahim Alabdulmohsin, Nicole Chiou, Alexander D'Amour, Arthur Gretton, Sanmi Koyejo, Matt J. Kusner, Stephen R. Pfohl, Olawale Salaudeen, Jessica Schrouff, Katherine Tsai

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Layer-Stack Temperature Scaling.

Amr Khalifa, Michael C. Mozer, Hanie Sedghi, Behnam Neyshabur, Ibrahim Alabdulmohsin

CoRR, 2022

Maintaining fairness across distribution shift: do we have viable solutions for real-world applications?

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

CoRR, 2022

Fair Wrapping for Black-box Predictions.

Alexander Soen, Ibrahim M. Alabdulmohsin, Sanmi Koyejo, Yishay Mansour, Nyalleng Moorosi, Richard Nock, Ke Sun, Lexing Xie

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Diagnosing failures of fairness transfer across distribution shift in real-world medical settings.

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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Reduction to Binary Approach for Debiasing Multiclass Datasets.

Ibrahim M. Alabdulmohsin, Jessica Schrouff, Sanmi Koyejo

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Revisiting Neural Scaling Laws in Language and Vision.

Ibrahim M. Alabdulmohsin, Behnam Neyshabur, Xiaohua Zhai

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

The Impact of Reinitialization on Generalization in Convolutional Neural Networks.

Ibrahim M. Alabdulmohsin, Hartmut Maennel, Daniel Keysers

CoRR, 2021

A Generalized Lottery Ticket Hypothesis.

Ibrahim M. Alabdulmohsin, Larisa Markeeva, Daniel Keysers, Ilya O. Tolstikhin

CoRR, 2021

A Generalization of Classical Formulas in Numerical Integration and Series Convergence Acceleration.

Ibrahim M. Alabdulmohsin

CoRR, 2021

A Near-Optimal Algorithm for Debiasing Trained Machine Learning Models.

Ibrahim M. Alabdulmohsin, Mario Lucic

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Towards a Unified Theory of Learning and Information.

Ibrahim M. Alabdulmohsin

Entropy, 2020

Fair Classification via Unconstrained Optimization.

Ibrahim M. Alabdulmohsin

CoRR, 2020

What Do Neural Networks Learn When Trained With Random Labels?

Hartmut Maennel, Ibrahim M. Alabdulmohsin, Ilya O. Tolstikhin, Robert J. N. Baldock, Olivier Bousquet, Sylvain Gelly, Daniel Keysers

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2018

Axiomatic Characterization of AdaBoost and the Multiplicative Weight Update Procedure.

Ibrahim M. Alabdulmohsin

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Information Theoretic Guarantees for Empirical Risk Minimization with Applications to Model Selection and Large-Scale Optimization.

Ibrahim M. Alabdulmohsin

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Learning via Query Synthesis.

Ibrahim Alabdulmohsin

PhD thesis, 2017

An Information-Theoretic Route from Generalization in Expectation to Generalization in Probability.

Ibrahim M. Alabdulmohsin

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

Large margin classification with indefinite similarities.

Ibrahim M. Alabdulmohsin, Moustapha Cissé, Xin Gao, Xiangliang Zhang

Mach. Learn., 2016

Uniform Generalization, Concentration, and Adaptive Learning.

Ibrahim M. Alabdulmohsin

CoRR, 2016

Is Attribute-Based Zero-Shot Learning an Ill-Posed Strategy?

Ibrahim M. Alabdulmohsin, Moustapha Cissé, Xiangliang Zhang

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Content-Agnostic Malware Detection in Heterogeneous Malicious Distribution Graph.

Ibrahim M. Alabdulmohsin, Yufei Han, Yun Shen, Xiangliang Zhang

Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016

2015

Algorithmic Stability and Uniform Generalization.

Ibrahim M. Alabdulmohsin

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Efficient Active Learning of Halfspaces via Query Synthesis.

Ibrahim M. Alabdulmohsin, Xin Gao, Xiangliang Zhang

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

A Mathematical Theory of Learning.

Ibrahim M. Alabdulmohsin

CoRR, 2014

End-to-end delay analysis in wireless sensor networks with service vacation.

Ibrahim M. Alabdulmohsin, Amal Hyadi, Laila H. Afify, Basem Shihada

Proceedings of the IEEE Wireless Communications and Networking Conference, 2014

Interference in wireless ad hoc networks with smart antennas.

Ibrahim M. Alabdulmohsin

Proceedings of the International Wireless Communications and Mobile Computing Conference, 2014

Adding Robustness to Support Vector Machines Against Adversarial Reverse Engineering.

Ibrahim M. Alabdulmohsin, Xin Gao, Xiangliang Zhang

Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014

Support vector machines with indefinite kernels.

Ibrahim M. Alabdulmohsin, Xin Gao, Xiangliang Zhang

Proceedings of the Sixth Asian Conference on Machine Learning, 2014