Model Reconstruction from Model Explanations

13 July 2018

Papers citing "Model Reconstruction from Model Explanations"

21 / 21 papers shown

Title
Examining the Threat Landscape: Foundation Models and Model Stealing Ankita Raj Deepankar Varma Chetan Arora AAML 270 1 0 25 Feb 2025
Cryptanalytic Extraction of Neural Network Models Nicholas Carlini Matthew Jagielski Ilya Mironov FedML MLAU MIACV AAML 130 135 0 10 Mar 2020
SNIFF: Reverse Engineering of Neural Networks with Fault Attacks J. Breier Dirmanto Jap Xiaolu Hou S. Bhasin Yang Liu 56 53 0 23 Feb 2020
Thieves on Sesame Street! Model Extraction of BERT-based APIs Kalpesh Krishna Gaurav Singh Tomar Ankur P. Parikh Nicolas Papernot Mohit Iyyer MIACV MLAU 110 201 0 27 Oct 2019
Privacy-preserving Prediction Cynthia Dwork Vitaly Feldman 58 91 0 27 Mar 2018
The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks Nicholas Carlini Chang-rui Liu Ulfar Erlingsson Jernej Kos Basel Alomair 144 1,143 0 22 Feb 2018
Spurious Local Minima are Common in Two-Layer ReLU Neural Networks Itay Safran Ohad Shamir 180 263 0 24 Dec 2017
SmoothGrad: removing noise by adding noise D. Smilkov Nikhil Thorat Been Kim F. Viégas Martin Wattenberg FAtt ODL 204 2,226 0 12 Jun 2017
Recovery Guarantees for One-hidden-layer Neural Networks Kai Zhong Zhao Song Prateek Jain Peter L. Bartlett Inderjit S. Dhillon MLT 175 337 0 10 Jun 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 188 5,989 0 04 Mar 2017
An Analytical Formula of Population Gradient for two-layered ReLU network and its Applications in Convergence and Critical Point Analysis Yuandong Tian MLT 192 216 0 02 Mar 2017
Membership Inference Attacks against Machine Learning Models Reza Shokri M. Stronati Congzheng Song Vitaly Shmatikov SLR MIALM MIACV 261 4,135 0 18 Oct 2016
Stealing Machine Learning Models via Prediction APIs Florian Tramèr Fan Zhang Ari Juels Michael K. Reiter Thomas Ristenpart SILM MLAU 107 1,807 0 09 Sep 2016
Practical Black-Box Attacks against Machine Learning Nicolas Papernot Patrick McDaniel Ian Goodfellow S. Jha Z. Berkay Celik A. Swami MLAU AAML 75 3,678 0 08 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,020 0 10 Dec 2015
Strategic Classification Moritz Hardt N. Megiddo Christos H. Papadimitriou Mary Wootters 77 371 0 23 Jun 2015
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 248 4,672 0 21 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.7K 100,386 0 04 Sep 2014
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 312 7,308 0 20 Dec 2013
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 595 15,893 0 12 Nov 2013
How to Explain Individual Classification Decisions D. Baehrens T. Schroeter Stefan Harmeling M. Kawanabe K. Hansen K. Müller FAtt 137 1,104 0 06 Dec 2009