v1v2v3v4v5 (latest)

Constrained Learning with Non-Convex Losses

8 March 2021

Alejandro Ribeiro

Papers citing "Constrained Learning with Non-Convex Losses"

45 / 45 papers shown

Title
Adversarial Robustness with Semi-Infinite Constrained Learning Alexander Robey Luiz F. O. Chamon George J. Pappas Hamed Hassani Alejandro Ribeiro AAML OOD 158 46 0 29 Oct 2021
Probably Approximately Correct Constrained Learning Luiz F. O. Chamon Alejandro Ribeiro 64 42 0 09 Jun 2020
SAT: Improving Adversarial Training via Curriculum-Based Loss Smoothing Chawin Sitawarin S. Chakraborty David Wagner AAML 54 39 0 18 Mar 2020
Attacks Which Do Not Kill Training Make Adversarial Learning Stronger Jingfeng Zhang Xilie Xu Bo Han Gang Niu Li-zhen Cui Masashi Sugiyama Mohan S. Kankanhalli AAML 58 404 0 26 Feb 2020
Precise Tradeoffs in Adversarial Training for Linear Regression Adel Javanmard Mahdi Soltanolkotabi Hamed Hassani AAML 60 109 0 24 Feb 2020
The empirical duality gap of constrained statistical learning Luiz F. O. Chamon Santiago Paternain Miguel Calvo-Fullana Alejandro Ribeiro 51 9 0 12 Feb 2020
Constrained Reinforcement Learning Has Zero Duality Gap Santiago Paternain Luiz F. O. Chamon Miguel Calvo-Fullana Alejandro Ribeiro 59 193 0 29 Oct 2019
Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers Hadi Salman Greg Yang Jungshian Li Pengchuan Zhang Huan Zhang Ilya P. Razenshteyn Sébastien Bubeck AAML 90 552 0 09 Jun 2019
Sparse multiresolution representations with adaptive kernels Maria Peifer Luiz F. O. Chamon Santiago Paternain Alejandro Ribeiro 39 4 0 07 May 2019
Invariance-Preserving Localized Activation Functions for Graph Neural Networks Luana Ruiz Fernando Gama A. Marques Alejandro Ribeiro GNN 72 53 0 29 Mar 2019
On Evaluating Adversarial Robustness Nicholas Carlini Anish Athalye Nicolas Papernot Wieland Brendel Jonas Rauber Dimitris Tsipras Ian Goodfellow Aleksander Madry Alexey Kurakin ELM AAML 109 905 0 18 Feb 2019
Certified Adversarial Robustness via Randomized Smoothing Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter AAML 171 2,052 0 08 Feb 2019
Theoretically Principled Trade-off between Robustness and Accuracy Hongyang R. Zhang Yaodong Yu Jiantao Jiao Eric Xing L. Ghaoui Michael I. Jordan 159 2,563 0 24 Jan 2019
Functional Nonlinear Sparse Models Luiz F. O. Chamon Yonina C. Eldar Alejandro Ribeiro 43 11 0 01 Nov 2018
Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals Andrew Cotter Heinrich Jiang S. Wang Taman Narayan Maya R. Gupta Seungil You Karthik Sridharan 84 158 0 11 Sep 2018
Learning Optimal Resource Allocations in Wireless Systems Mark Eisen Clark Zhang Luiz F. O. Chamon Daniel D. Lee Alejandro Ribeiro 67 208 0 21 Jul 2018
Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints Andrew Cotter Maya R. Gupta Heinrich Jiang Nathan Srebro Karthik Sridharan S. Wang Blake E. Woodworth Seungil You FaML 82 105 0 29 Jun 2018
Robustness May Be at Odds with Accuracy Dimitris Tsipras Shibani Santurkar Logan Engstrom Alexander Turner Aleksander Madry AAML 110 1,785 0 30 May 2018
A Reductions Approach to Fair Classification Alekh Agarwal A. Beygelzimer Miroslav Dudík John Langford Hanna M. Wallach FaML 230 1,105 0 06 Mar 2018
Empirical Risk Minimization under Fairness Constraints Michele Donini L. Oneto Shai Ben-David John Shawe-Taylor Massimiliano Pontil FaML 80 445 0 23 Feb 2018
A Semantic Loss Function for Deep Learning with Symbolic Knowledge Jingyi Xu Zilu Zhang Tal Friedman Yitao Liang Guy Van den Broeck 107 453 0 29 Nov 2017
Learning Steerable Filters for Rotation Equivariant CNNs Maurice Weiler Fred Hamprecht M. Storath 102 388 0 20 Nov 2017
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness Michael Kearns Seth Neel Aaron Roth Zhiwei Steven Wu FaML 202 784 0 14 Nov 2017
Learning One-hidden-layer Neural Networks with Landscape Design Rong Ge Jason D. Lee Tengyu Ma MLT 208 262 0 01 Nov 2017
Certifying Some Distributional Robustness with Principled Adversarial Training Aman Sinha Hongseok Namkoong Riccardo Volpi John C. Duchi OOD 127 865 0 29 Oct 2017
Theoretical insights into the optimization landscape of over-parameterized shallow neural networks Mahdi Soltanolkotabi Adel Javanmard Jason D. Lee 187 423 0 16 Jul 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 319 12,151 0 19 Jun 2017
A Closer Look at Memorization in Deep Networks Devansh Arpit Stanislaw Jastrzebski Nicolas Ballas David M. Krueger Emmanuel Bengio ... Tegan Maharaj Asja Fischer Aaron Courville Yoshua Bengio Simon Lacoste-Julien TDI 131 1,829 0 16 Jun 2017
A Convex Framework for Fair Regression R. Berk Hoda Heidari S. Jabbari Matthew Joseph Michael Kearns Jamie Morgenstern Seth Neel Aaron Roth FaML 125 342 0 07 Jun 2017
Constrained Policy Optimization Joshua Achiam David Held Aviv Tamar Pieter Abbeel 134 1,335 0 30 May 2017
Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs Alon Brutzkus Amir Globerson MLT 176 313 0 26 Feb 2017
Rotation equivariant vector field networks Diego Marcos Michele Volpi N. Komodakis D. Tuia 73 270 0 29 Dec 2016
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 351 4,636 0 10 Nov 2016
Categorical Reparameterization with Gumbel-Softmax Eric Jang S. Gu Ben Poole BDL 363 5,390 0 03 Nov 2016
The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables Chris J. Maddison A. Mnih Yee Whye Teh BDL 200 2,541 0 02 Nov 2016
Warped Convolutions: Efficient Invariance to Spatial Transformations João F. Henriques Andrea Vedaldi 68 116 0 14 Sep 2016
Satisfying Real-world Goals with Dataset Constraints Gabriel Goh Andrew Cotter Maya R. Gupta M. Friedlander OffRL 70 215 0 24 Jun 2016
Improving the Robustness of Deep Neural Networks via Stability Training Stephan Zheng Yang Song Thomas Leung Ian Goodfellow OOD 58 639 0 15 Apr 2016
Group Equivariant Convolutional Networks Taco S. Cohen Max Welling BDL 176 1,946 0 24 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.3K 194,641 0 10 Dec 2015
Learning with a Strong Adversary Ruitong Huang Bing Xu Dale Schuurmans Csaba Szepesvári AAML 88 358 0 10 Nov 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.1K 150,433 0 22 Dec 2014
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 282 19,145 0 20 Dec 2014
Automated Experiments on Ad Privacy Settings: A Tale of Opacity, Choice, and Discrimination Amit Datta Michael Carl Tschantz Anupam Datta 87 735 0 27 Aug 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 291 14,968 1 21 Dec 2013