Samira Shabanian

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 15

Top Topics

Data Collection

Multiplicative Noise Removal

Pruning Algorithm

Mathematical Expressions

Top Venues

Publications

Abdelrahman Zayed, Gonçalo Mordido, Samira Shabanian, Ioana Baldini, Sarath Chandar
Fairness-Aware Structured Pruning in Transformers. AAAI (2024)
Abdelrahman Zayed, Gonçalo Mordido, Samira Shabanian, Ioana Baldini, Sarath Chandar
Fairness-Aware Structured Pruning in Transformers. CoRR (2023)
Meng Cao, Mehdi Fatemi, Jackie CK Cheung, Samira Shabanian
Systematic Rectification of Language Models via Dead-end Analysis. ICLR (2023)
Abdelrahman Zayed, Prasanna Parthasarathi, Gonçalo Mordido, Hamid Palangi, Samira Shabanian, Sarath Chandar
Deep Learning on a Healthy Data Diet: Finding Important Examples for Fairness. AAAI (2023)
Abdelrahman Zayed, Gonçalo Mordido, Samira Shabanian, Sarath Chandar
Should We Attend More or Less? Modulating Attention for Fairness. CoRR (2023)
Meng Cao, Mehdi Fatemi, Jackie Chi Kit Cheung, Samira Shabanian
Systematic Rectification of Language Models via Dead-end Analysis. CoRR (2023)
Meng Cao, Mehdi Fatemi, Jackie Chi Kit Cheung, Samira Shabanian
Successor Features for Efficient Multisubject Controlled Text Generation. CoRR (2023)
Divya Shanmugam, Fernando Diaz, Samira Shabanian, Michele Finck, Asia Biega
Learning to Limit Data Collection via Scaling Laws: A Computational Interpretation for the Legal Principle of Data Minimization. FAccT (2022)
Abdelrahman Zayed, Prasanna Parthasarathi, Gonçalo Mordido, Hamid Palangi, Samira Shabanian, Sarath Chandar
Deep Learning on a Healthy Data Diet: Finding Important Examples for Fairness. CoRR (2022)
Charan Reddy, Deepak Sharma, Soroush Mehri, Adriana Romero-Soriano, Samira Shabanian, Sina Honari
Benchmarking Bias Mitigation Algorithms in Representation Learning through Fairness Metrics. NeurIPS Datasets and Benchmarks (2021)
Divya Shanmugam, Samira Shabanian, Fernando Diaz, Michèle Finck, Asia Biega
Learning to Limit Data Collection via Scaling Laws: Data Minimization Compliance in Practice. CoRR (2021)
Remi Tachet des Combes, Mohammad Pezeshki, Samira Shabanian, Aaron C. Courville, Yoshua Bengio
On the Learning Dynamics of Deep Neural Networks. CoRR (2018)
Samira Shabanian, Devansh Arpit, Adam Trischler, Yoshua Bengio
Variational Bi-LSTMs. CoRR (2017)
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
Theano: A Python framework for fast computation of mathematical expressions. CoRR (2016)
Jörg Bornschein, Samira Shabanian, Asja Fischer, Yoshua Bengio
Bidirectional Helmholtz Machines. ICML (2016)
Jörg Bornschein, Samira Shabanian, Asja Fischer, Yoshua Bengio
Training opposing directed models using geometric mean matching. CoRR (2015)