Interpretable Neural Networks with Frank-Wolfe: Sparse Relevance Maps and Relevance Orderings

15 October 2021

Papers citing "Interpretable Neural Networks with Frank-Wolfe: Sparse Relevance Maps and Relevance Orderings"

30 / 30 papers shown

Title
SAIF: Sparse Adversarial and Imperceptible Attack Framework Tooba Imtiaz Morgan Kohler Jared Miller Zifeng Wang Octavia Camps Mario Sznaier Octavia Camps Jennifer Dy AAML 55 0 0 14 Dec 2022
Complexity of Linear Minimization and Projection on Some Sets Cyrille W. Combettes Sebastian Pokutta 24 39 0 25 Jan 2021
A Survey on Neural Network Interpretability Yu Zhang Peter Tiño A. Leonardis K. Tang FaML XAI 168 671 0 28 Dec 2020
Deep Neural Network Training with Frank-Wolfe Sebastian Pokutta Christoph Spiegel Max Zimmer 26 24 0 14 Oct 2020
Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization Geoffrey Negiar Gideon Dresdner Alicia Y. Tsai L. Ghaoui Francesco Locatello Robert M. Freund Fabian Pedregosa 37 24 0 27 Feb 2020
On Interpretability of Artificial Neural Networks: A Survey Fenglei Fan Jinjun Xiong Mengzhou Li Ge Wang AAML AI4CE 54 304 0 08 Jan 2020
Feature relevance quantification in explainable AI: A causal problem Dominik Janzing Lenon Minorics Patrick Blobaum FAtt CML 35 279 0 29 Oct 2019
A Rate-Distortion Framework for Explaining Neural Network Decisions Jan Macdonald S. Wäldchen Sascha Hauch Gitta Kutyniok 31 40 0 27 May 2019
Stochastic Conditional Gradient++ Hamed Hassani Amin Karbasi Aryan Mokhtari Zebang Shen 31 22 0 19 Feb 2019
Deep Frank-Wolfe For Neural Network Optimization Leonard Berrada Andrew Zisserman M. P. Kumar ODL 25 40 0 19 Nov 2018
Explaining Explanations: An Overview of Interpretability of Machine Learning Leilani H. Gilpin David Bau Ben Z. Yuan Ayesha Bajwa Michael A. Specter Lalana Kagal XAI 70 1,849 0 31 May 2018
Stochastic Conditional Gradient Methods: From Convex Minimization to Submodular Maximization Aryan Mokhtari Hamed Hassani Amin Karbasi 41 113 0 24 Apr 2018
Deep Learning for Medical Image Analysis Mina Rezaei Haojin Yang Christoph Meinel 57 2,047 0 17 Aug 2017
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 265 2,248 0 24 Jun 2017
SmoothGrad: removing noise by adding noise D. Smilkov Nikhil Thorat Been Kim F. Viégas Martin Wattenberg FAtt ODL 179 2,211 0 12 Jun 2017
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 422 129,831 0 12 Jun 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 405 21,459 0 22 May 2017
Interpretable Explanations of Black Boxes by Meaningful Perturbation Ruth C. Fong Andrea Vedaldi FAtt AAML 45 1,514 0 11 Apr 2017
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 343 3,742 0 28 Feb 2017
Lazifying Conditional Gradient Algorithms Gábor Braun Sebastian Pokutta Daniel Zink 34 50 0 17 Oct 2016
Stochastic Frank-Wolfe Methods for Nonconvex Optimization Sashank J. Reddi S. Sra Barnabás Póczós Alex Smola 47 139 0 27 Jul 2016
Convergence Rate of Frank-Wolfe for Non-Convex Objectives Simon Lacoste-Julien 53 194 0 01 Jul 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 478 16,765 0 16 Feb 2016
Variance-Reduced and Projection-Free Stochastic Optimization Elad Hazan Haipeng Luo 37 165 0 05 Feb 2016
On the Global Linear Convergence of Frank-Wolfe Optimization Variants Simon Lacoste-Julien Martin Jaggi 52 410 0 18 Nov 2015
Evaluating the visualization of what a Deep Neural Network has learned Wojciech Samek Alexander Binder G. Montavon Sebastian Lapuschkin K. Müller XAI 99 1,189 0 21 Sep 2015
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 159 4,653 0 21 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 822 99,991 0 04 Sep 2014
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation Kyunghyun Cho B. V. Merrienboer Çağlar Gülçehre Dzmitry Bahdanau Fethi Bougares Holger Schwenk Yoshua Bengio AIMat 582 23,235 0 03 Jun 2014
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 152 7,252 0 20 Dec 2013