no code implementations • 8 Jun 2023 • Kai Jia, Pasapol Saowakon, Limor Appelbaum, Martin Rinard
We take a formal approach to the explainability problem of machine learning systems.
no code implementations • 21 Apr 2023 • Kai Jia, Martin Rinard
$L_0$ regularization of neural networks is a fundamental problem.
no code implementations • 15 Jan 2023 • Kai Jia, Hongwen Zhang, Liang An, Yebin Liu
The key components of a typical regressor lie in the feature extraction of input views and the fusion of multi-view features.
no code implementations • 18 Aug 2021 • Kai Jia, Martin Rinard
We propose to prepend an input quantization layer to the network.
1 code implementation • 1 Jan 2021 • Weihao Gao, Xiangjun Fan, Jiankai Sun, Kai Jia, Wenzhi Xiao, Chong Wang, Xiaobing Liu
With the model learnt, a beam search over the latent codes is performed to retrieve the top candidates.
1 code implementation • 12 Jul 2020 • Weihao Gao, Xiangjun Fan, Chong Wang, Jiankai Sun, Kai Jia, Wenzhi Xiao, Ruofan Ding, Xingyan Bin, Hui Yang, Xiaobing Liu
With the model learnt, a beam search over the structure is performed to retrieve the top candidates for reranking.
1 code implementation • NeurIPS 2020 • Kai Jia, Martin Rinard
We present a new system, EEV, for efficient and exact verification of BNNs.
1 code implementation • 6 Mar 2020 • Kai Jia, Martin Rinard
For a pretrained neural network, we present a method that efficiently searches inputs as witnesses for the incorrectness of robustness claims made by a complete verifier.
6 code implementations • CVPR 2018 • Chao Peng, Tete Xiao, Zeming Li, Yuning Jiang, Xiangyu Zhang, Kai Jia, Gang Yu, Jian Sun
The improvements in recent CNN-based object detection works, from R-CNN [11], Fast/Faster R-CNN [10, 31] to recent Mask R-CNN [14] and RetinaNet [24], mainly come from new network, new framework, or novel loss design.
1 code implementation • 9 May 2016 • The Theano Development Team, Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermueller, 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 Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Mélanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian Goodfellow, Matt Graham, Caglar Gulcehre, 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 Lefrancois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert T. McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher 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 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
Since its introduction, it has been one of the most used CPU and GPU mathematical compilers - especially in the machine learning community - and has shown steady performance improvements.