ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1908.10796
  4. Cited By
Multi-Objective Automatic Machine Learning with AutoxgboostMC
v1v2 (latest)

Multi-Objective Automatic Machine Learning with AutoxgboostMC

28 August 2019
Florian Pfisterer
Stefan Coors
Janek Thomas
J. Herbinger
ArXiv (abs)PDFHTML

Papers citing "Multi-Objective Automatic Machine Learning with AutoxgboostMC"

10 / 10 papers shown
VirnyFlow: A Design Space for Responsible Model Development
VirnyFlow: A Design Space for Responsible Model Development
Denys Herasymuk
Nazar Protsiv
Julia Stoyanovich
200
0
0
02 Jun 2025
A knowledge-driven AutoML architecture
A knowledge-driven AutoML architecture
C. Cofaru
Johan Loeckx
250
0
0
28 Nov 2023
One Model Many Scores: Using Multiverse Analysis to Prevent Fairness
  Hacking and Evaluate the Influence of Model Design Decisions
One Model Many Scores: Using Multiverse Analysis to Prevent Fairness Hacking and Evaluate the Influence of Model Design DecisionsConference on Fairness, Accountability and Transparency (FAccT), 2023
Jan Simson
Florian Pfisterer
Christoph Kern
360
16
0
31 Aug 2023
Can Fairness be Automated? Guidelines and Opportunities for
  Fairness-aware AutoML
Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoMLJournal of Artificial Intelligence Research (JAIR), 2023
Hilde J. P. Weerts
Florian Pfisterer
Matthias Feurer
Katharina Eggensperger
Eddie Bergman
Noor H. Awad
Joaquin Vanschoren
Mykola Pechenizkiy
J. Herbinger
Katharina Eggensperger
FaML
429
25
0
15 Mar 2023
Out of Context: Investigating the Bias and Fairness Concerns of
  "Artificial Intelligence as a Service"
Out of Context: Investigating the Bias and Fairness Concerns of "Artificial Intelligence as a Service"International Conference on Human Factors in Computing Systems (CHI), 2023
Kornel Lewicki
M. S. Lee
Jennifer Cobbe
Jatinder Singh
301
33
0
02 Feb 2023
Multi-Objective Hyperparameter Optimization in Machine Learning -- An
  Overview
Multi-Objective Hyperparameter Optimization in Machine Learning -- An OverviewACM Transactions on Evolutionary Learning and Optimization (TELO), 2022
Florian Karl
Tobias Pielok
Julia Moosbauer
Florian Pfisterer
Stefan Coors
...
Jakob Richter
Michel Lang
Eduardo C. Garrido-Merchán
Juergen Branke
J. Herbinger
AI4CE
368
93
0
15 Jun 2022
Towards Green Automated Machine Learning: Status Quo and Future
  Directions
Towards Green Automated Machine Learning: Status Quo and Future DirectionsJournal of Artificial Intelligence Research (JAIR), 2021
Tanja Tornede
Alexander Tornede
Jonas Hanselle
Marcel Wever
F. Mohr
Eyke Hüllermeier
430
47
0
10 Nov 2021
Multi-Objective Evolutionary Design of Composite Data-Driven Models
Multi-Objective Evolutionary Design of Composite Data-Driven ModelsIEEE Congress on Evolutionary Computation (CEC), 2021
Iana S. Polonskaia
Nikolay O. Nikitin
I. Revin
Pavel Vychuzhanin
Anna V. Kaluzhnaya
380
10
0
01 Mar 2021
Fair Bayesian Optimization
Fair Bayesian Optimization
Valerio Perrone
Michele Donini
Muhammad Bilal Zafar
Robin Schmucker
K. Kenthapadi
Cédric Archambeau
FaML
311
90
0
09 Jun 2020
Billion-scale similarity search with GPUs
Billion-scale similarity search with GPUsIEEE Transactions on Big Data (TBD), 2017
Jeff Johnson
Matthijs Douze
Edouard Grave
1.1K
4,753
0
28 Feb 2017
1
Page 1 of 1