Samira Shabanian

According to our database, Samira Shabanian authored at least 13 papers between 2015 and 2024.

Collaborative distances:

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

2024

Fairness-Aware Structured Pruning in Transformers.

Abdelrahman Zayed, Gonçalo Mordido, Samira Shabanian, Ioana Baldini, Sarath Chandar

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Successor Features for Efficient Multisubject Controlled Text Generation.

Meng Cao, Mehdi Fatemi, Jackie Chi Kit Cheung, Samira Shabanian

CoRR, 2023

Should We Attend More or Less? Modulating Attention for Fairness.

Abdelrahman Zayed, Gonçalo Mordido, Samira Shabanian, Sarath Chandar

CoRR, 2023

Systematic Rectification of Language Models via Dead-end Analysis.

Meng Cao, Mehdi Fatemi, Jackie C. K. Cheung, Samira Shabanian

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Deep Learning on a Healthy Data Diet: Finding Important Examples for Fairness.

Abdelrahman Zayed, Prasanna Parthasarathi, Gonçalo Mordido, Hamid Palangi, Samira Shabanian, Sarath Chandar

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Learning to Limit Data Collection via Scaling Laws: A Computational Interpretation for the Legal Principle of Data Minimization.

Divya Shanmugam, Fernando Diaz, Samira Shabanian, Michèle Finck, Asia Biega

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

2021

Learning to Limit Data Collection via Scaling Laws: Data Minimization Compliance in Practice.

Divya Shanmugam, Samira Shabanian, Fernando Diaz, Michèle Finck, Asia Biega

CoRR, 2021

Benchmarking Bias Mitigation Algorithms in Representation Learning through Fairness Metrics.

Charan Reddy, Deepak Sharma, Soroush Mehri, Adriana Romero-Soriano, Samira Shabanian, Sina Honari

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

2018

On the Learning Dynamics of Deep Neural Networks.

Remi Tachet des Combes, Mohammad Pezeshki, Samira Shabanian, Aaron C. Courville, Yoshua Bengio

CoRR, 2018

2017

Variational Bi-LSTMs.

Samira Shabanian, Devansh Arpit, Adam Trischler, Yoshua Bengio

CoRR, 2017

2016

Theano: A Python framework for fast computation of mathematical expressions.

Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermüller, Dzmitry Bahdanau, Nicolas Ballas, Frédéric Bastien, Justin Bayer, Anatoly Belikov, Alexander Belopolsky, Yoshua Bengio, Arnaud Bergeron, James Bergstra, Valentin Bisson, Josh Bleecher Snyder, Nicolas Bouchard, Nicolas Boulanger-Lewandowski, Xavier Bouthillier, Alexandre de Brébisson, Olivier Breuleux, Pierre Luc Carrier, Kyunghyun Cho, Jan Chorowski, Paul F. Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron C. Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Melanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian J. Goodfellow, Matthew Graham, Çaglar Gülçehre, Philippe Hamel, Iban Harlouchet, Jean-Philippe Heng, Balázs Hidasi, Sina Honari, Arjun Jain, Sébastien Jean, Kai Jia, Mikhail Korobov, Vivek Kulkarni, Alex Lamb, Pascal Lamblin, Eric Larsen, César Laurent, Sean Lee, Simon Lefrançois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher Joseph Pal, Razvan Pascanu, Mohammad Pezeshki, Colin Raffel, Daniel Renshaw, Matthew Rocklin, Adriana Romero, Markus Roth, Peter Sadowski, John Salvatier, François Savard, Jan Schlüter, John Schulman, Gabriel Schwartz, Iulian Vlad Serban, Dmitriy Serdyuk, Samira Shabanian, Étienne Simon, Sigurd Spieckermann, S. Ramana Subramanyam, Jakub Sygnowski, Jérémie Tanguay, Gijs van Tulder, Joseph P. Turian, Sebastian Urban, Pascal Vincent, Francesco Visin, Harm de Vries, David Warde-Farley, Dustin J. Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, Ying Zhang

CoRR, 2016

Bidirectional Helmholtz Machines.

Jörg Bornschein, Samira Shabanian, Asja Fischer, Yoshua Bengio

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Training opposing directed models using geometric mean matching.

Jörg Bornschein, Samira Shabanian, Asja Fischer, Yoshua Bengio

CoRR, 2015