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FairPilot: An Explorative System for Hyperparameter Tuning through the
  Lens of Fairness

FairPilot: An Explorative System for Hyperparameter Tuning through the Lens of Fairness

10 April 2023
Francesco Di Carlo
Nazanin Nezami
Hadis Anahideh
Abolfazl Asudeh
ArXiv (abs)PDFHTML

Papers citing "FairPilot: An Explorative System for Hyperparameter Tuning through the Lens of Fairness"

15 / 15 papers shown
Title
Bayesian Optimization is Superior to Random Search for Machine Learning
  Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020
Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020
Ryan Turner
David Eriksson
M. McCourt
J. Kiili
Eero Laaksonen
Zhen Xu
Isabelle M Guyon
BDL
76
303
0
20 Apr 2021
Fairness in Machine Learning
Fairness in Machine Learning
L. Oneto
Silvia Chiappa
FaML
299
500
0
31 Dec 2020
Accuracy and Fairness Trade-offs in Machine Learning: A Stochastic
  Multi-Objective Approach
Accuracy and Fairness Trade-offs in Machine Learning: A Stochastic Multi-Objective Approach
Suyun Liu
Luis Nunes Vicente
FaML
65
71
0
03 Aug 2020
Importance of Tuning Hyperparameters of Machine Learning Algorithms
Importance of Tuning Hyperparameters of Machine Learning Algorithms
Hilde J. P. Weerts
A. Mueller
Joaquin Vanschoren
54
110
0
15 Jul 2020
Open Source Software for Efficient and Transparent Reviews
Open Source Software for Efficient and Transparent Reviews
R. Schoot
J. D. Bruin
Raoul Schram
Parisa Zahedi
J. D. Boer
...
Yongchao Ma
Qixiang Fang
Sybren Hindriks
L. Tummers
Daniel L. Oberski
68
520
0
22 Jun 2020
Verifying Individual Fairness in Machine Learning Models
Verifying Individual Fairness in Machine Learning Models
Philips George John
Deepak Vijaykeerthy
Diptikalyan Saha
FaML
60
59
0
21 Jun 2020
Fair Bayesian Optimization
Fair Bayesian Optimization
Valerio Perrone
Michele Donini
Muhammad Bilal Zafar
Robin Schmucker
K. Kenthapadi
Cédric Archambeau
FaML
67
86
0
09 Jun 2020
Balancing Competing Objectives with Noisy Data: Score-Based Classifiers
  for Welfare-Aware Machine Learning
Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning
Esther Rolf
Max Simchowitz
Sarah Dean
Lydia T. Liu
Daniel Björkegren
Moritz Hardt
J. Blumenstock
43
23
0
15 Mar 2020
Hyper-Parameter Optimization: A Review of Algorithms and Applications
Hyper-Parameter Optimization: A Review of Algorithms and Applications
Tong Yu
Hong Zhu
AAML
81
540
0
12 Mar 2020
Teaching Responsible Data Science: Charting New Pedagogical Territory
Teaching Responsible Data Science: Charting New Pedagogical Territory
Julia Stoyanovich
Armanda Lewis
43
38
0
23 Dec 2019
A Survey on Bias and Fairness in Machine Learning
A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi
Fred Morstatter
N. Saxena
Kristina Lerman
Aram Galstyan
SyDaFaML
574
4,391
0
23 Aug 2019
An Intersectional Definition of Fairness
An Intersectional Definition of Fairness
James R. Foulds
Rashidul Islam
Kamrun Naher Keya
Shimei Pan
FaML
75
191
0
22 Jul 2018
Inherent Trade-Offs in the Fair Determination of Risk Scores
Inherent Trade-Offs in the Fair Determination of Risk Scores
Jon M. Kleinberg
S. Mullainathan
Manish Raghavan
FaML
122
1,783
0
19 Sep 2016
On the relation between accuracy and fairness in binary classification
On the relation between accuracy and fairness in binary classification
Indrė Žliobaitė
FaML
80
198
0
21 May 2015
Hyperparameter Search in Machine Learning
Hyperparameter Search in Machine Learning
Marc Claesen
B. De Moor
88
442
0
07 Feb 2015
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