Jeremiah J. Harmsen

According to our database, Jeremiah J. Harmsen authored at least 11 papers between 2003 and 2023.

Collaborative distances:

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

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

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

2022

UViM: A Unified Modeling Approach for Vision with Learned Guiding Codes.

Alexander Kolesnikov, André Susano Pinto, Lucas Beyer, Xiaohua Zhai, Jeremiah Harmsen, Neil Houlsby

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

2021

RLDS: an Ecosystem to Generate, Share and Use Datasets in Reinforcement Learning.

Sabela Ramos, Sertan Girgin, Léonard Hussenot, Damien Vincent, Hanna Yakubovich, Daniel Toyama, Anita Gergely, Piotr Stanczyk, Raphaël Marinier, Jeremiah Harmsen, Olivier Pietquin, Nikola Momchev

CoRR, 2021

2017

TensorFlow-Serving: Flexible, High-Performance ML Serving.

Christopher Olston, Noah Fiedel, Kiril Gorovoy, Jeremiah Harmsen, Li Lao, Fangwei Li, Vinu Rajashekhar, Sukriti Ramesh, Jordan Soyke

CoRR, 2017

2016

Wide & Deep Learning for Recommender Systems.

Heng-Tze Cheng, Levent Koc, Jeremiah Harmsen, Tal Shaked, Tushar Chandra, Hrishi Aradhye, Glen Anderson, Greg Corrado, Wei Chai, Mustafa Ispir, Rohan Anil, Zakaria Haque, Lichan Hong, Vihan Jain, Xiaobing Liu, Hemal Shah

Proceedings of the 1st Workshop on Deep Learning for Recommender Systems, 2016

2014

Up next: retrieval methods for large scale related video suggestion.

Michael Bendersky, Lluis Garcia Pueyo, Jeremiah J. Harmsen, Vanja Josifovski, Dima Lepikhin

Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

2009

Capacity of Steganographic Channels.

Jeremiah J. Harmsen, William A. Pearlman

IEEE Trans. Inf. Theory, 2009

2004

Kernel Fisher discriminant for steganalysis of JPEG hiding methods.

Jeremiah J. Harmsen, William A. Pearlman

Proceedings of the Security, Steganography, and Watermarking of Multimedia Contents VI, 2004

Fast additive noise steganalysis.

Jeremiah J. Harmsen, Kevin D. Bowers, William A. Pearlman

Proceedings of the Security, Steganography, and Watermarking of Multimedia Contents VI, 2004

2003

Steganalysis of additive-noise modelable information hiding.

Jeremiah J. Harmsen, William A. Pearlman

Proceedings of the Security and Watermarking of Multimedia Contents V, 2003