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2001.06509
Cited By
Trust in AutoML: Exploring Information Needs for Establishing Trust in Automated Machine Learning Systems
International Conference on Intelligent User Interfaces (IUI), 2020
17 January 2020
Jaimie Drozdal
Justin D. Weisz
Dakuo Wang
Gaurav Dass
Bingsheng Yao
Changruo Zhao
Michael J. Muller
Lin Ju
Hui Su
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Papers citing
"Trust in AutoML: Exploring Information Needs for Establishing Trust in Automated Machine Learning Systems"
50 / 50 papers shown
DeepCAVE: A Visualization and Analysis Tool for Automated Machine Learning
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01 Dec 2025
AutoML in Cybersecurity: An Empirical Study
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198
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28 Sep 2025
From Hazard Identification to Controller Design: Proactive and LLM-Supported Safety Engineering for ML-Powered Systems
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Christopher S. Timperley
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515
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11 Feb 2025
Large Language Models for Constructing and Optimizing Machine Learning Workflows: A Survey
Yang Gu
Hengyu You
Jian Cao
Muran Yu
Haoran Fan
Shiyou Qian
LM&MA
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481
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11 Nov 2024
R+R:Understanding Hyperparameter Effects in DP-SGD
Asia-Pacific Computer Systems Architecture Conference (ACSA), 2024
Felix Morsbach
J. Reubold
T. Strufe
333
1
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04 Nov 2024
Towards certifiable AI in aviation: landscape, challenges, and opportunities
Hymalai Bello
Daniel Geißler
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Stefan Muller-Divéky
Peter Muller
Shannon Kittrell
Mengxi Liu
Bo Zhou
Paul Lukowicz
242
1
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13 Sep 2024
How Mature is Requirements Engineering for AI-based Systems? A Systematic Mapping Study on Practices, Challenges, and Future Research Directions
Requirements Engineering (RE), 2024
Umm-e- Habiba
Markus Haug
Justus Bogner
Stefan Wagner
300
23
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11 Sep 2024
Position: A Call to Action for a Human-Centered AutoML Paradigm
Marius Lindauer
Florian Karl
A. Klier
Julia Moosbauer
Alexander Tornede
Andreas Mueller
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Matthias Feurer
Bernd Bischl
293
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05 Jun 2024
Towards Feature Engineering with Human and AI's Knowledge: Understanding Data Science Practitioners' Perceptions in Human&AI-Assisted Feature Engineering Design
Qian Zhu
Dakuo Wang
Shuai Ma
April Yi Wang
Zixin Chen
Udayan Khurana
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310
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23 May 2024
Deciphering AutoML Ensembles: cattleia's Assistance in Decision-Making
Anna Kozak
Dominik Kedzierski
Jakub Piwko
Malwina Wojewoda
Katarzyna Wo'znica
204
1
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19 Mar 2024
Automated data processing and feature engineering for deep learning and big data applications: a survey
Journal of Information and Intelligence (JII), 2024
A. Mumuni
F. Mumuni
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18 Mar 2024
Healthcare Voice AI Assistants: Factors Influencing Trust and Intention to Use
Xiao Zhan
Noura Abdi
William Seymour
Jose Such
313
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09 Jan 2024
Integration Of Evolutionary Automated Machine Learning With Structural Sensitivity Analysis For Composite Pipelines
Nikolay O. Nikitin
Maiia Pinchuk
Valerii Pokrovskii
Peter Shevchenko
Andrey Getmanov
Yaroslav Aksenkin
I. Revin
Andrey Stebenkov
Ekaterina Poslavskaya
Anna V. Kaluzhnaya
232
0
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22 Dec 2023
Trust, distrust, and appropriate reliance in (X)AI: a survey of empirical evaluation of user trust
Roel W. Visser
Tobias M. Peters
Ingrid Scharlau
Barbara Hammer
210
11
0
04 Dec 2023
A knowledge-driven AutoML architecture
C. Cofaru
Johan Loeckx
290
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28 Nov 2023
On the Hyperparameter Loss Landscapes of Machine Learning Models: An Exploratory Study
Knowledge Discovery and Data Mining (KDD), 2023
Mingyu Huang
Ke Li
309
5
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23 Nov 2023
How Good is ChatGPT in Giving Advice on Your Visualization Design?
Nam Wook Kim
Grace Myers
Benjamin Bach
585
39
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14 Oct 2023
DCNFIS: Deep Convolutional Neuro-Fuzzy Inference System
Mojtaba Yeganejou
Kimia Honari
Ryan Kluzinski
S. Dick
M. Lipsett
James Miller
FedML
AI4CE
235
5
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11 Aug 2023
Identifying Explanation Needs of End-users: Applying and Extending the XAI Question Bank
Message Understanding Conference (MUC), 2023
Lars Sipos
Ulrike Schäfer
Katrin Glinka
Claudia Muller-Birn
217
18
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18 Jul 2023
Beyond Labels: Empowering Human Annotators with Natural Language Explanations through a Novel Active-Learning Architecture
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023
Bingsheng Yao
Ishan Jindal
Lucian Popa
Yannis Katsis
Sayan Ghosh
...
Yuxuan Lu
Shashank Srivastava
Yunyao Li
James A. Hendler
Dakuo Wang
297
14
0
22 May 2023
Investigating and Designing for Trust in AI-powered Code Generation Tools
Conference on Fairness, Accountability and Transparency (FAccT), 2023
Ruotong Wang
Ruijia Cheng
Denae Ford
Thomas Zimmermann
278
97
0
18 May 2023
Humans, AI, and Context: Understanding End-Users' Trust in a Real-World Computer Vision Application
Conference on Fairness, Accountability and Transparency (FAccT), 2023
Sunnie S. Y. Kim
E. A. Watkins
Olga Russakovsky
Ruth C. Fong
Andrés Monroy-Hernández
240
48
0
15 May 2023
Why is AI not a Panacea for Data Workers? An Interview Study on Human-AI Collaboration in Data Storytelling
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2023
Haotian Li
Yun Wang
Q. V. Liao
Huamin Qu
362
30
0
17 Apr 2023
Tracing and Visualizing Human-ML/AI Collaborative Processes through Artifacts of Data Work
International Conference on Human Factors in Computing Systems (CHI), 2023
Jennifer Rogers
Anamaria Crisan
236
13
0
05 Apr 2023
AutoML in The Wild: Obstacles, Workarounds, and Expectations
International Conference on Human Factors in Computing Systems (CHI), 2023
Yuan Sun
Qiurong Song
Xinning Gui
Fenglong Ma
Ting Wang
326
32
0
21 Feb 2023
"It would work for me too": How Online Communities Shape Software Developers' Trust in AI-Powered Code Generation Tools
Ruijia Cheng
Ruotong Wang
Thomas Zimmermann
Denae Ford
289
46
0
07 Dec 2022
An Empirical Study on the Usage of Automated Machine Learning Tools
IEEE International Conference on Software Maintenance and Evolution (ICSME), 2022
Forough Majidi
Moses Openja
Foutse Khomh
Heng Li
306
18
0
28 Aug 2022
A Survey of Open Source Automation Tools for Data Science Predictions
Nicholas Hoell
236
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24 Aug 2022
D-BIAS: A Causality-Based Human-in-the-Loop System for Tackling Algorithmic Bias
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2022
Bhavya Ghai
Klaus Mueller
200
54
0
10 Aug 2022
DeepCAVE: An Interactive Analysis Tool for Automated Machine Learning
René Sass
Eddie Bergman
André Biedenkapp
Katharina Eggensperger
Marius Lindauer
340
20
0
07 Jun 2022
Lodestar: Supporting Independent Learning and Rapid Experimentation Through Data-Driven Analysis Recommendations
Deepthi Raghunandan
Zhe Cui
K. Sivaramakrishnan
Segen Tirfe
Shenzhi Shi
Tejaswi Darshan Shrestha
Leilani Battle
Niklas Elmqvist
158
11
0
16 Apr 2022
Telling Stories from Computational Notebooks: AI-Assisted Presentation Slides Creation for Presenting Data Science Work
International Conference on Human Factors in Computing Systems (CHI), 2022
Chengbo Zheng
Dakuo Wang
A. Wang
Xiaojuan Ma
343
64
0
21 Mar 2022
Practitioner Motives to Use Different Hyperparameter Optimization Methods
ACM Transactions on Computer-Human Interaction (TOCHI), 2022
Niclas Kannengießer
Niklas Hasebrook
Felix Morsbach
Marc-André Zöller
Jörg Franke
Marius Lindauer
Katharina Eggensperger
Ali Sunyaev
404
4
0
03 Mar 2022
XAutoML: A Visual Analytics Tool for Understanding and Validating Automated Machine Learning
Marc-André Zöller
Waldemar Titov
T. Schlegel
Marco F. Huber
HAI
486
19
0
24 Feb 2022
Better Together? An Evaluation of AI-Supported Code Translation
International Conference on Intelligent User Interfaces (IUI), 2022
Justin D. Weisz
Michael J. Muller
Steven I. Ross
Fernando Martinez
Stephanie Houde
Mayank Agarwal
Kartik Talamadupula
John T. Richards
235
90
0
15 Feb 2022
Naive Automated Machine Learning
Machine-mediated learning (ML), 2021
F. Mohr
Marcel Wever
292
19
0
29 Nov 2021
Explaining Hyperparameter Optimization via Partial Dependence Plots
Julia Moosbauer
J. Herbinger
Giuseppe Casalicchio
Marius Lindauer
B. Bischl
302
93
0
08 Nov 2021
Human-Centered AI for Data Science: A Systematic Approach
Dakuo Wang
Xiaojuan Ma
A. Wang
201
4
0
03 Oct 2021
Automatic Componentwise Boosting: An Interpretable AutoML System
Stefan Coors
Daniel Schalk
J. Herbinger
David Rügamer
TPM
302
5
0
12 Sep 2021
Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges
J. Herbinger
Martin Binder
Michel Lang
Tobias Pielok
Jakob Richter
...
Theresa Ullmann
Marc Becker
A. Boulesteix
Difan Deng
Marius Lindauer
468
862
0
13 Jul 2021
Naive Automated Machine Learning -- A Late Baseline for AutoML
F. Mohr
Marcel Wever
216
0
0
18 Mar 2021
Documentation Matters: Human-Centered AI System to Assist Data Science Code Documentation in Computational Notebooks
A. Wang
Dakuo Wang
Jaimie Drozdal
Michael J. Muller
Soya Park
Justin D. Weisz
Xuye Liu
Lingfei Wu
Casey Dugan
485
86
0
24 Feb 2021
Whither AutoML? Understanding the Role of Automation in Machine Learning Workflows
International Conference on Human Factors in Computing Systems (CHI), 2021
Doris Xin
Eva Yiwei Wu
D. Lee
Niloufar Salehi
Aditya G. Parameswaran
298
111
0
13 Jan 2021
Fits and Starts: Enterprise Use of AutoML and the Role of Humans in the Loop
International Conference on Human Factors in Computing Systems (CHI), 2021
Anamaria Crisan
Brittany Fiore-Gartland
258
63
0
12 Jan 2021
"Brilliant AI Doctor" in Rural China: Tensions and Challenges in AI-Powered CDSS Deployment
International Conference on Human Factors in Computing Systems (CHI), 2021
Dakuo Wang
Liuping Wang
Zhan Zhang
Ding Wang
Haiyi Zhu
Yvonne Gao
Xiangmin Fan
Feng Tian
273
194
0
04 Jan 2021
AutonoML: Towards an Integrated Framework for Autonomous Machine Learning
D. Kedziora
Katarzyna Musial
Bogdan Gabrys
330
19
0
23 Dec 2020
Teaching to Learn: Sequential Teaching of Agents with Inner States
M. Çelikok
Pierre-Alexandre Murena
Samuel Kaski
105
0
0
14 Sep 2020
Trust-Based Cloud Machine Learning Model Selection For Industrial IoT and Smart City Services
IEEE Internet of Things Journal (IEEE IoT J.), 2020
Basheer Qolomany
Ihab Mohammed
Ala I. Al-Fuqaha
Mohsen Guizani
Junaid Qadir
202
40
0
11 Aug 2020
The Impact of Explanations on AI Competency Prediction in VQA
Kamran Alipour
Arijit Ray
Xiaoyu Lin
J. Schulze
Yi Yao
Giedrius Burachas
287
12
0
02 Jul 2020
How to Support Users in Understanding Intelligent Systems? Structuring the Discussion
International Conference on Intelligent User Interfaces (IUI), 2020
Malin Eiband
Daniel Buschek
H. Hussmann
304
30
0
22 Jan 2020
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