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The Dimpled Manifold Model of Adversarial Examples in Machine Learning

18 June 2021

Papers citing "The Dimpled Manifold Model of Adversarial Examples in Machine Learning"

33 / 33 papers shown

Title
Generalizability vs. Counterfactual Explainability Trade-Off Fabiano Veglianti Flavio Giorgi Fabrizio Silvestri Gabriele Tolomei 40 0 0 29 May 2025
An Analytical Characterization of Sloppiness in Neural Networks: Insights from Linear Models Jialin Mao Itay Griniasty Yan Sun Mark K. Transtrum James P. Sethna Pratik Chaudhari 105 0 0 13 May 2025
Exploring Gradient-Guided Masked Language Model to Detect Textual Adversarial Attacks Xiaomei Zhang Zhaoxi Zhang Yanjun Zhang Xufei Zheng L. Zhang Shengshan Hu Shirui Pan AAML 58 0 0 08 Apr 2025
Adversarial Vulnerability as a Consequence of On-Manifold Inseparibility Rajdeep Haldar Yue Xing Qifan Song Guang Lin 50 0 0 09 Oct 2024
ALIF: Low-Cost Adversarial Audio Attacks on Black-Box Speech Platforms using Linguistic Features Peng Cheng Yuwei Wang Peng Huang Zhongjie Ba Xiaodong Lin Feng Lin Liwang Lu Kui Ren AAML 74 9 0 03 Aug 2024
MALT Powers Up Adversarial Attacks Odelia Melamed Gilad Yehudai Adi Shamir AAML 49 0 0 02 Jul 2024
Persistent Classification: A New Approach to Stability of Data and Adversarial Examples Brian Bell Michael Geyer David Glickenstein Keaton Hamm C. Scheidegger Amanda S. Fernandez Juston Moore AAML 87 1 0 11 Apr 2024
Generative Kaleidoscopic Networks H. Shrivastava 62 0 0 19 Feb 2024
Adversarial Robustness Through Artifact Design Tsufit Shua Mahmood Sharif AAML 72 0 0 07 Feb 2024
Explaining high-dimensional text classifiers Odelia Melamed Rich Caruana 43 0 0 22 Nov 2023
Sensitivity-Aware Amortized Bayesian Inference Lasse Elsemüller Hans Olischläger Marvin Schmitt Paul-Christian Bürkner Ullrich Kothe Stefan T. Radev 118 9 0 17 Oct 2023
On the Computational Entanglement of Distant Features in Adversarial Machine Learning Yen-Lung Lai Xingbo Dong Zhe Jin AAML 59 0 0 27 Sep 2023
Projected Randomized Smoothing for Certified Adversarial Robustness Samuel Pfrommer Brendon G. Anderson Somayeh Sojoudi AAML 71 16 0 25 Sep 2023
How adversarial attacks can disrupt seemingly stable accurate classifiers Oliver J. Sutton Qinghua Zhou I. Tyukin Alexander N. Gorban Alexander Bastounis D. Higham AAML 69 1 0 07 Sep 2023
Masked Language Model Based Textual Adversarial Example Detection Xiaomei Zhang Zhaoxi Zhang Qi Zhong Xufei Zheng Yanjun Zhang Shengshan Hu L. Zhang AAML 101 2 0 18 Apr 2023
The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networks Spencer Frei Gal Vardi Peter L. Bartlett Nathan Srebro 83 17 0 02 Mar 2023
Adversarial Examples Exist in Two-Layer ReLU Networks for Low Dimensional Linear Subspaces Odelia Melamed Gilad Yehudai Gal Vardi GAN 60 2 0 01 Mar 2023
Out-of-Distribution Detection with Reconstruction Error and Typicality-based Penalty Genki Osada Tsubasa Takahashi Budrul Ahsan Takashi Nishide OODD 92 14 0 24 Dec 2022
Textual Manifold-based Defense Against Natural Language Adversarial Examples D. M. Nguyen Anh Tuan Luu AAML 84 17 0 05 Nov 2022
Do Perceptually Aligned Gradients Imply Adversarial Robustness? Roy Ganz Bahjat Kawar Michael Elad AAML 45 10 0 22 Jul 2022
Threat Model-Agnostic Adversarial Defense using Diffusion Models Tsachi Blau Roy Ganz Bahjat Kawar Alex M. Bronstein Michael Elad AAML DiffM 95 27 0 17 Jul 2022
On the Principles of Parsimony and Self-Consistency for the Emergence of Intelligence Yi Ma Doris Y. Tsao H. Shum 142 78 0 11 Jul 2022
A law of adversarial risk, interpolation, and label noise Daniel Paleka Amartya Sanyal NoLa AAML 94 10 0 08 Jul 2022
Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks Huishuai Zhang Da Yu Yiping Lu Di He AAML 98 1 0 09 Jun 2022
Adversarial Reprogramming Revisited Matthias Englert R. Lazic AAML 98 11 0 07 Jun 2022
An Analytic Framework for Robust Training of Artificial Neural Networks Ramin Barati Reza Safabakhsh Mohammad Rahmati AAML 56 0 0 26 May 2022
Topology and geometry of data manifold in deep learning German Magai A. Ayzenberg AAML 67 11 0 19 Apr 2022
Planting Undetectable Backdoors in Machine Learning Models S. Goldwasser Michael P. Kim Vinod Vaikuntanathan Or Zamir AAML 56 73 0 14 Apr 2022
AdvEst: Adversarial Perturbation Estimation to Classify and Detect Adversarial Attacks against Speaker Identification Sonal Joshi Saurabh Kataria Jesus Villalba Najim Dehak AAML 86 7 0 08 Apr 2022
Gradient Methods Provably Converge to Non-Robust Networks Gal Vardi Gilad Yehudai Ohad Shamir 95 28 0 09 Feb 2022
Probabilistically Robust Learning: Balancing Average- and Worst-case Performance Alexander Robey Luiz F. O. Chamon George J. Pappas Hamed Hassani AAML OOD 109 43 0 02 Feb 2022
The Security of Deep Learning Defences for Medical Imaging Mosh Levy Guy Amit Yuval Elovici Yisroel Mirsky AAML MedIm 141 9 0 21 Jan 2022
Do Input Gradients Highlight Discriminative Features? Harshay Shah Prateek Jain Praneeth Netrapalli AAML FAtt 120 59 0 25 Feb 2021