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Robust Decision Trees Against Adversarial Examples

Robust Decision Trees Against Adversarial Examples

27 February 2019
Hongge Chen
Huan Zhang
Duane S. Boning
Cho-Jui Hsieh
    AAML
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Papers citing "Robust Decision Trees Against Adversarial Examples"

50 / 57 papers shown
Title
Des-q: a quantum algorithm to provably speedup retraining of decision trees
Des-q: a quantum algorithm to provably speedup retraining of decision trees
Niraj Kumar
Romina Yalovetzky
Changhao Li
Pierre Minssen
Marco Pistoia
53
4
0
03 Jan 2025
Cultivating Archipelago of Forests: Evolving Robust Decision Trees
  through Island Coevolution
Cultivating Archipelago of Forests: Evolving Robust Decision Trees through Island Coevolution
A. Żychowski
Andrew Perrault
Jacek Mańdziuk
59
0
0
18 Dec 2024
Learning Decision Trees and Forests with Algorithmic Recourse
Learning Decision Trees and Forests with Algorithmic Recourse
Kentaro Kanamori
Takuya Takagi
Ken Kobayashi
Yuichi Ike
48
3
0
03 Jun 2024
Output-Constrained Decision Trees
Output-Constrained Decision Trees
cS. .Ilker Birbil
Douganay Ozese
Mustafa Baydougan
24
0
0
24 May 2024
Verifiable Boosted Tree Ensembles
Verifiable Boosted Tree Ensembles
Stefano Calzavara
Lorenzo Cazzaro
Claudio Lucchese
Giulio Ermanno Pibiri
AAML
44
0
0
22 Feb 2024
Faster Repeated Evasion Attacks in Tree Ensembles
Faster Repeated Evasion Attacks in Tree Ensembles
Lorenzo Cascioli
Laurens Devos
Ondvrej Kuvzelka
Jesse Davis
AAML
13
0
0
13 Feb 2024
Robustness Verification for Knowledge-Based Logic of Risky Driving
  Scenes
Robustness Verification for Knowledge-Based Logic of Risky Driving Scenes
Xia Wang
Anda Liang
Jonathan Sprinkle
Taylor T. Johnson
26
4
0
27 Dec 2023
Coevolutionary Algorithm for Building Robust Decision Trees under
  Minimax Regret
Coevolutionary Algorithm for Building Robust Decision Trees under Minimax Regret
A. Żychowski
Andrew Perrault
Jacek Mańdziuk
AAML
11
1
0
14 Dec 2023
Learning Optimal Classification Trees Robust to Distribution Shifts
Learning Optimal Classification Trees Robust to Distribution Shifts
Nathan Justin
S. Aghaei
Andrés Gómez
P. Vayanos
OOD
42
0
0
26 Oct 2023
SoK: Realistic Adversarial Attacks and Defenses for Intelligent Network
  Intrusion Detection
SoK: Realistic Adversarial Attacks and Defenses for Intelligent Network Intrusion Detection
João Vitorino
Isabel Praça
Eva Maia
AAML
30
22
0
13 Aug 2023
Symmetry Defense Against XGBoost Adversarial Perturbation Attacks
Symmetry Defense Against XGBoost Adversarial Perturbation Attacks
Blerta Lindqvist
AAML
43
0
0
10 Aug 2023
Interpretable Differencing of Machine Learning Models
Interpretable Differencing of Machine Learning Models
Swagatam Haldar
Diptikalyan Saha
Dennis L. Wei
Rahul Nair
Elizabeth M. Daly
16
1
0
10 Jun 2023
Transferable Adversarial Robustness for Categorical Data via Universal
  Robust Embeddings
Transferable Adversarial Robustness for Categorical Data via Universal Robust Embeddings
Klim Kireev
Maksym Andriushchenko
Carmela Troncoso
Nicolas Flammarion
OOD
35
1
0
06 Jun 2023
Verifiable Learning for Robust Tree Ensembles
Verifiable Learning for Robust Tree Ensembles
Stefano Calzavara
Lorenzo Cazzaro
Giulio Ermanno Pibiri
N. Prezza
AAML
23
3
0
05 May 2023
Towards Adversarial Realism and Robust Learning for IoT Intrusion
  Detection and Classification
Towards Adversarial Realism and Robust Learning for IoT Intrusion Detection and Classification
João Vitorino
Isabel Praça
Eva Maia
AAML
37
28
0
30 Jan 2023
Robust Boosting Forests with Richer Deep Feature Hierarchy
Robust Boosting Forests with Richer Deep Feature Hierarchy
Jianqiao Wangni
3DPC
35
0
0
29 Oct 2022
A.I. Robustness: a Human-Centered Perspective on Technological
  Challenges and Opportunities
A.I. Robustness: a Human-Centered Perspective on Technological Challenges and Opportunities
Andrea Tocchetti
Lorenzo Corti
Agathe Balayn
Mireia Yurrita
Philip Lippmann
Marco Brambilla
Jie Yang
32
10
0
17 Oct 2022
Adversarial Robustness for Tabular Data through Cost and Utility
  Awareness
Adversarial Robustness for Tabular Data through Cost and Utility Awareness
Klim Kireev
B. Kulynych
Carmela Troncoso
AAML
26
16
0
27 Aug 2022
SoK: Explainable Machine Learning for Computer Security Applications
SoK: Explainable Machine Learning for Computer Security Applications
A. Nadeem
D. Vos
Clinton Cao
Luca Pajola
Simon Dieck
Robert Baumgartner
S. Verwer
34
40
0
22 Aug 2022
Quantifying probabilistic robustness of tree-based classifiers against
  natural distortions
Quantifying probabilistic robustness of tree-based classifiers against natural distortions
Christoph Schweimer
S. Scher
41
0
0
22 Aug 2022
Provably Adversarially Robust Nearest Prototype Classifiers
Provably Adversarially Robust Nearest Prototype Classifiers
Václav Voráček
Matthias Hein
AAML
20
11
0
14 Jul 2022
Threat Assessment in Machine Learning based Systems
Threat Assessment in Machine Learning based Systems
L. Tidjon
Foutse Khomh
27
17
0
30 Jun 2022
Adversarial Example Detection in Deployed Tree Ensembles
Adversarial Example Detection in Deployed Tree Ensembles
Laurens Devos
Wannes Meert
Jesse Davis
AAML
15
1
0
27 Jun 2022
Integrity Authentication in Tree Models
Integrity Authentication in Tree Models
Weijie Zhao
Yingjie Lao
Ping Li
59
5
0
30 May 2022
(De-)Randomized Smoothing for Decision Stump Ensembles
(De-)Randomized Smoothing for Decision Stump Ensembles
Miklós Z. Horváth
Mark Niklas Muller
Marc Fischer
Martin Vechev
30
3
0
27 May 2022
AdIoTack: Quantifying and Refining Resilience of Decision Tree Ensemble
  Inference Models against Adversarial Volumetric Attacks on IoT Networks
AdIoTack: Quantifying and Refining Resilience of Decision Tree Ensemble Inference Models against Adversarial Volumetric Attacks on IoT Networks
Arman Pashamokhtari
Gustavo E. A. P. A. Batista
Hassan Habibi Gharakheili
AAML
31
9
0
18 Mar 2022
Adaptative Perturbation Patterns: Realistic Adversarial Learning for
  Robust Intrusion Detection
Adaptative Perturbation Patterns: Realistic Adversarial Learning for Robust Intrusion Detection
João Vitorino
Nuno Oliveira
Isabel Praça
AAML
27
28
0
08 Mar 2022
Adversarial Attack and Defense for Non-Parametric Two-Sample Tests
Adversarial Attack and Defense for Non-Parametric Two-Sample Tests
Xilie Xu
Jingfeng Zhang
Feng Liu
Masashi Sugiyama
Mohan S. Kankanhalli
AAML
30
1
0
07 Feb 2022
Beyond Robustness: Resilience Verification of Tree-Based Classifiers
Beyond Robustness: Resilience Verification of Tree-Based Classifiers
Stefano Calzavara
Lorenzo Cazzaro
Claudio Lucchese
Federico Marcuzzi
S. Orlando
AAML
43
9
0
05 Dec 2021
Certifying Robustness to Programmable Data Bias in Decision Trees
Certifying Robustness to Programmable Data Bias in Decision Trees
Anna P. Meyer
Aws Albarghouthi
Loris Dántoni
27
21
0
08 Oct 2021
Robust Optimal Classification Trees Against Adversarial Examples
Robust Optimal Classification Trees Against Adversarial Examples
D. Vos
S. Verwer
AAML
6
21
0
08 Sep 2021
Trustworthy AI: A Computational Perspective
Trustworthy AI: A Computational Perspective
Haochen Liu
Yiqi Wang
Wenqi Fan
Xiaorui Liu
Yaxin Li
Shaili Jain
Yunhao Liu
Anil K. Jain
Jiliang Tang
FaML
104
196
0
12 Jul 2021
A Review of Formal Methods applied to Machine Learning
A Review of Formal Methods applied to Machine Learning
Caterina Urban
Antoine Miné
41
55
0
06 Apr 2021
Individually Fair Gradient Boosting
Individually Fair Gradient Boosting
Alexander Vargo
Fan Zhang
Mikhail Yurochkin
Yuekai Sun
FaML
FedML
24
15
0
31 Mar 2021
Connecting Interpretability and Robustness in Decision Trees through
  Separation
Connecting Interpretability and Robustness in Decision Trees through Separation
Michal Moshkovitz
Yao-Yuan Yang
Kamalika Chaudhuri
33
22
0
14 Feb 2021
Fair Training of Decision Tree Classifiers
Fair Training of Decision Tree Classifiers
Francesco Ranzato
Caterina Urban
Marco Zanella
FaML
14
12
0
04 Jan 2021
Genetic Adversarial Training of Decision Trees
Genetic Adversarial Training of Decision Trees
Francesco Ranzato
Marco Zanella
22
14
0
21 Dec 2020
Efficient Training of Robust Decision Trees Against Adversarial Examples
Efficient Training of Robust Decision Trees Against Adversarial Examples
D. Vos
S. Verwer
AAML
6
36
0
18 Dec 2020
Versatile Verification of Tree Ensembles
Versatile Verification of Tree Ensembles
Laurens Devos
Wannes Meert
Jesse Davis
AAML
22
12
0
26 Oct 2020
An Efficient Adversarial Attack for Tree Ensembles
An Efficient Adversarial Attack for Tree Ensembles
Chong Zhang
Huan Zhang
Cho-Jui Hsieh
AAML
10
23
0
22 Oct 2020
Embedding and Extraction of Knowledge in Tree Ensemble Classifiers
Embedding and Extraction of Knowledge in Tree Ensemble Classifiers
Wei Huang
Xingyu Zhao
Xiaowei Huang
AAML
11
11
0
16 Oct 2020
On $\ell_p$-norm Robustness of Ensemble Stumps and Trees
On ℓp\ell_pℓp​-norm Robustness of Ensemble Stumps and Trees
Yihan Wang
Huan Zhang
Hongge Chen
Duane S. Boning
Cho-Jui Hsieh
AAML
15
7
0
20 Aug 2020
Certifying Decision Trees Against Evasion Attacks by Program Analysis
Certifying Decision Trees Against Evasion Attacks by Program Analysis
Stefano Calzavara
Pietro Ferrara
Claudio Lucchese
AAML
24
10
0
06 Jul 2020
Opportunities and Challenges in Deep Learning Adversarial Robustness: A
  Survey
Opportunities and Challenges in Deep Learning Adversarial Robustness: A Survey
S. Silva
Peyman Najafirad
AAML
OOD
28
131
0
01 Jul 2020
Evaluations and Methods for Explanation through Robustness Analysis
Evaluations and Methods for Explanation through Robustness Analysis
Cheng-Yu Hsieh
Chih-Kuan Yeh
Xuanqing Liu
Pradeep Ravikumar
Seungyeon Kim
Sanjiv Kumar
Cho-Jui Hsieh
XAI
17
58
0
31 May 2020
Spanning Attack: Reinforce Black-box Attacks with Unlabeled Data
Spanning Attack: Reinforce Black-box Attacks with Unlabeled Data
Lu Wang
Huan Zhang
Jinfeng Yi
Cho-Jui Hsieh
Yuan Jiang
AAML
35
12
0
11 May 2020
AN-GCN: An Anonymous Graph Convolutional Network Defense Against
  Edge-Perturbing Attack
AN-GCN: An Anonymous Graph Convolutional Network Defense Against Edge-Perturbing Attack
Ao Liu
Beibei Li
Tao Li
Pan Zhou
Rui Wang
AAML
27
0
0
06 May 2020
Feature Partitioning for Robust Tree Ensembles and their Certification
  in Adversarial Scenarios
Feature Partitioning for Robust Tree Ensembles and their Certification in Adversarial Scenarios
Stefano Calzavara
Claudio Lucchese
Federico Marcuzzi
S. Orlando
AAML
16
9
0
07 Apr 2020
When are Non-Parametric Methods Robust?
When are Non-Parametric Methods Robust?
Robi Bhattacharjee
Kamalika Chaudhuri
AAML
44
27
0
13 Mar 2020
Cost-Aware Robust Tree Ensembles for Security Applications
Cost-Aware Robust Tree Ensembles for Security Applications
Yizheng Chen
Shiqi Wang
Weifan Jiang
Asaf Cidon
Suman Jana
AAML
OOD
14
5
0
03 Dec 2019
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