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Inverse Classification with Limited Budget and Maximum Number of
  Perturbed Samples

Inverse Classification with Limited Budget and Maximum Number of Perturbed Samples

29 September 2020
Jaehoon Koo
Diego Klabjan
J. Utke
ArXivPDFHTML

Papers citing "Inverse Classification with Limited Budget and Maximum Number of Perturbed Samples"

5 / 5 papers shown
Title
GLANCE: Global Actions in a Nutshell for Counterfactual Explainability
GLANCE: Global Actions in a Nutshell for Counterfactual Explainability
Ioannis Emiris
Dimitris Fotakis
G. Giannopoulos
Dimitrios Gunopulos
Loukas Kavouras
...
D. Rontogiannis
Dimitris Sacharidis
Nikolaos Theologitis
Dimitrios Tomaras
Konstantinos Tsopelas
CML
FAtt
38
1
0
29 May 2024
Counterfactual Explanations and Algorithmic Recourses for Machine
  Learning: A Review
Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review
Sahil Verma
Varich Boonsanong
Minh Hoang
Keegan E. Hines
John P. Dickerson
Chirag Shah
CML
28
164
0
20 Oct 2020
Unified recurrent neural network for many feature types
Unified recurrent neural network for many feature types
Alexander Stec
Diego Klabjan
J. Utke
AI4TS
27
2
0
24 Sep 2018
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
368
5,849
0
08 Jul 2016
Recurrent Neural Networks for Multivariate Time Series with Missing
  Values
Recurrent Neural Networks for Multivariate Time Series with Missing Values
Zhengping Che
S. Purushotham
Kyunghyun Cho
David Sontag
Yan Liu
AI4TS
249
1,903
0
06 Jun 2016
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