Adversarial Active Learning for Deep Networks: a Margin Based Approach

Adversarial Active Learning for Deep Networks: a Margin Based Approach

27 February 2018

Mélanie Ducoffe

Papers citing "Adversarial Active Learning for Deep Networks: a Margin Based Approach"

18 / 18 papers shown

Title
RADEP: A Resilient Adaptive Defense Framework Against Model Extraction Attacks Amit Chakraborty Sayyed Farid Ahamed Sandip Roy S. Banerjee Kevin Choi A. Rahman Alison Hu Edward Bowen Sachin Shetty AAML 21 0 0 25 May 2025
A Coreset Selection of Coreset Selection Literature: Introduction and Recent Advances Brian B. Moser Arundhati S. Shanbhag Stanislav Frolov Federico Raue Joachim Folz Andreas Dengel 136 0 0 23 May 2025
Deep Active Learning in the Open World Tian Xie Jifan Zhang Haoyue Bai R. Nowak VLM 326 1 0 10 Nov 2024
ATOM: Attention Mixer for Efficient Dataset Distillation Samir Khaki A. Sajedi Kai Wang Lucy Z. Liu Y. Lawryshyn Konstantinos N. Plataniotis 100 3 0 02 May 2024
Less is more: sampling chemical space with active learning Justin S. Smith B. Nebgen Nicholas Lubbers Olexandr Isayev A. Roitberg 49 607 0 28 Jan 2018
Active Learning for Visual Question Answering: An Empirical Study Xiaoyu Lin Devi Parikh 65 31 0 06 Nov 2017
Deep Active Learning for Named Entity Recognition Yanyao Shen Hyokun Yun Zachary Chase Lipton Y. Kronrod Anima Anandkumar HAI 74 455 0 19 Jul 2017
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods Nicholas Carlini D. Wagner AAML 103 1,851 0 20 May 2017
Active Decision Boundary Annotation with Deep Generative Models Miriam W. Huijser Jan van Gemert 40 46 0 20 Mar 2017
Deep Bayesian Active Learning with Image Data Y. Gal Riashat Islam Zoubin Ghahramani BDL UQCV 56 1,725 0 08 Mar 2017
Cost-Effective Active Learning for Deep Image Classification Keze Wang Dongyu Zhang Ya Li Ruimao Zhang Liang Lin VLM 71 677 0 13 Jan 2017
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 170 8,513 0 16 Aug 2016
Defensive Distillation is Not Robust to Adversarial Examples Nicholas Carlini D. Wagner 35 339 0 14 Jul 2016
Theano: A Python framework for fast computation of mathematical expressions The Theano Development Team Rami Al-Rfou Guillaume Alain Amjad Almahairi Christof Angermüller ... Kelvin Xu Lijun Xue Li Yao Saizheng Zhang Ying Zhang 135 2,338 0 09 May 2016
QBDC: Query by dropout committee for training deep supervised architecture Mélanie Ducoffe F. Precioso OOD MU 23 19 0 19 Nov 2015
DeepFool: a simple and accurate method to fool deep neural networks Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi P. Frossard AAML 95 4,878 0 14 Nov 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 176 18,922 0 20 Dec 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 185 14,831 1 21 Dec 2013