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From Explanation to Action: An End-to-End Human-in-the-loop Framework
  for Anomaly Reasoning and Management

From Explanation to Action: An End-to-End Human-in-the-loop Framework for Anomaly Reasoning and Management

6 April 2023
Xueying Ding
Nikita Seleznev
Senthil Kumar
C. Bayan Bruss
Leman Akoglu
ArXiv (abs)PDFHTML

Papers citing "From Explanation to Action: An End-to-End Human-in-the-loop Framework for Anomaly Reasoning and Management"

16 / 16 papers shown
Title
Sparx: Distributed Outlier Detection at Scale
Sparx: Distributed Outlier Detection at Scale
Sean Zhang
V. Ursekar
Leman Akoglu
45
7
0
02 Jun 2022
Rethinking Explainability as a Dialogue: A Practitioner's Perspective
Rethinking Explainability as a Dialogue: A Practitioner's Perspective
Himabindu Lakkaraju
Dylan Slack
Yuxin Chen
Chenhao Tan
Sameer Singh
LRM
71
64
0
03 Feb 2022
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective
Satyapriya Krishna
Tessa Han
Alex Gu
Steven Wu
S. Jabbari
Himabindu Lakkaraju
246
195
0
03 Feb 2022
MTV: Visual Analytics for Detecting, Investigating, and Annotating
  Anomalies in Multivariate Time Series
MTV: Visual Analytics for Detecting, Investigating, and Annotating Anomalies in Multivariate Time Series
Dongyu Liu
Sarah Alnegheimish
Alexandra Zytek
K. Veeramachaneni
AI4TS
56
21
0
10 Dec 2021
HURRA! Human readable router anomaly detection
HURRA! Human readable router anomaly detection
J. M. Navarro
Dario Rossi
51
6
0
23 Jul 2021
A Survey on the Explainability of Supervised Machine Learning
A Survey on the Explainability of Supervised Machine Learning
Nadia Burkart
Marco F. Huber
FaMLXAI
55
775
0
16 Nov 2020
TODS: An Automated Time Series Outlier Detection System
TODS: An Automated Time Series Outlier Detection System
Kwei-Harng Lai
Daochen Zha
Guanchu Wang
Junjie Xu
Yue Zhao
...
Yile Chen
Purav Zumkhawaka
Minyang Wan
D. Martinez
Xia Hu
AI4TS
121
67
0
18 Sep 2020
How Useful Are the Machine-Generated Interpretations to General Users? A
  Human Evaluation on Guessing the Incorrectly Predicted Labels
How Useful Are the Machine-Generated Interpretations to General Users? A Human Evaluation on Guessing the Incorrectly Predicted Labels
Hua Shen
Ting-Hao 'Kenneth' Huang
FAttHAI
60
56
0
26 Aug 2020
CloudDet: Interactive Visual Analysis of Anomalous Performances in Cloud
  Computing Systems
CloudDet: Interactive Visual Analysis of Anomalous Performances in Cloud Computing Systems
Ke Xu
Yun Wang
Leni Yang
Yifang Wang
Bo Qiao
Si Qin
Yong Xu
Haidong Zhang
Huamin Qu
40
37
0
30 Jul 2019
Visual Analytics of Anomalous User Behaviors: A Survey
Visual Analytics of Anomalous User Behaviors: A Survey
Yang Shi
Yuyin Liu
Hanghang Tong
Jingrui He
Gang Yan
Nan Cao
43
22
0
14 May 2019
Anomaly Detection in Road Traffic Using Visual Surveillance: A Survey
Anomaly Detection in Road Traffic Using Visual Surveillance: A Survey
Santhosh Kelathodi Kumaran
D. P. Dogra
P. Roy
59
136
0
24 Jan 2019
PyOD: A Python Toolbox for Scalable Outlier Detection
PyOD: A Python Toolbox for Scalable Outlier Detection
Yue Zhao
Zain Nasrullah
Zheng Li
92
724
0
06 Jan 2019
VAE with a VampPrior
VAE with a VampPrior
Jakub M. Tomczak
Max Welling
GANBDL
68
635
0
19 May 2017
Deep Unsupervised Clustering with Gaussian Mixture Variational
  Autoencoders
Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders
Nat Dilokthanakul
P. Mediano
M. Garnelo
M. J. Lee
Hugh Salimbeni
Kai Arulkumaran
Murray Shanahan
DRL
74
658
0
08 Nov 2016
Categorical Reparameterization with Gumbel-Softmax
Categorical Reparameterization with Gumbel-Softmax
Eric Jang
S. Gu
Ben Poole
BDL
346
5,379
0
03 Nov 2016
Auto-Encoding Variational Bayes
Auto-Encoding Variational Bayes
Diederik P. Kingma
Max Welling
BDL
455
16,923
0
20 Dec 2013
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