Christoph Kern

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All published works
Action Title Year Authors
+ PDF Chat Confidential Computing Transparency 2024 Ceren Kocaoğullar
Tina Marjanov
Ivan Petrov
Ben Laurie
Al Cutter
Christoph Kern
Alice Hutchings
Alastair R. Beresford
+ PDF Chat When Small Decisions Have Big Impact: Fairness Implications of Algorithmic Profiling Schemes 2024 Christoph Kern
Ruben L. Bach
Hannah Mautner
Frauke Kreuter
+ PDF Chat The Missing Link: Allocation Performance in Causal Machine Learning 2024 Unai Fischer-Abaigar
Christoph Kern
Frauke Kreuter
+ PDF Chat One Model Many Scores: Using Multiverse Analysis to Prevent Fairness Hacking and Evaluate the Influence of Model Design Decisions 2024 Jan Simson
Florian Pfisterer
Christoph Kern
+ PDF Chat Lazy Data Practices Harm Fairness Research 2024 Jan Simson
Alessandro Fabris
Christoph Kern
+ PDF Chat Multi-CATE: Multi-Accurate Conditional Average Treatment Effect Estimation Robust to Unknown Covariate Shifts 2024 Christoph Kern
Michael Kim
Angela Zhou
+ PDF Chat Lazy Data Practices Harm Fairness Research 2024 Jan Simson
Alessandro Fabris
Christoph Kern
+ PDF Chat Latent Variable Forests for Latent Variable Score Estimation 2024 Franz Classe
Christoph Kern
+ PDF Chat Connecting Algorithmic Fairness to Quality Dimensions in Machine Learning in Official Statistics and Survey Production 2024 Patrick Oliver Schenk
Christoph Kern
+ Network Navigation with Online Delays is PSPACE-complete 2023 Thomas Depian
Christoph Kern
Sebastian Röder
Soeren Terziadis
Markus Wallinger
+ Everything, Everywhere All in One Evaluation: Using Multiverse Analysis to Evaluate the Influence of Model Design Decisions on Algorithmic Fairness 2023 Jan Simson
Florian Pfisterer
Christoph Kern
+ PDF Chat The impact of modeling decisions in statistical profiling 2023 Ruben L. Bach
Christoph Kern
Hannah Mautner
Frauke Kreuter
+ Bridging the Gap: Towards an Expanded Toolkit for ML-Supported Decision-Making in the Public Sector 2023 Unai Fischer Abaigar
Christoph Kern
Noam Barda
Frauke Kreuter
+ Annotation Sensitivity: Training Data Collection Methods Affect Model Performance 2023 Christoph Kern
Stephanie Eckman
Jacob Beck
Rob Chew
Bolei Ma
Frauke Kreuter
+ Minimizing Corners in Colored Rectilinear Grids 2023 Thomas Depian
Alexander Dobler
Christoph Kern
Jules Wulms
+ Annotation Sensitivity: Training Data Collection Methods Affect Model Performance 2023 Christoph Kern
Stephanie Eckman
Jacob Beck
Rob Chew
Bolei Ma
Frauke Kreuter
+ Universal adaptability: Target-independent inference that competes with propensity scoring 2022 Michael P. Kim
Christoph Kern
Shafi Goldwasser
Frauke Kreuter
Omer Reingold
+ Uncertainty-aware predictive modeling for fair data-driven decisions 2022 Patrick Kaiser
Christoph Kern
David Rügamer
+ Distributive Justice and Fairness Metrics in Automated Decision-making: How Much Overlap Is There? 2021 Matthias Kuppler
Christoph Kern
Ruben L. Bach
Frauke Kreuter
+ Fairness in Algorithmic Profiling: A German Case Study 2021 Christoph Kern
Ruben L. Bach
Hannah Mautner
Frauke Kreuter
+ Distributive Justice and Fairness Metrics in Automated Decision-making: How Much Overlap Is There? 2021 Matthias Kuppler
Christoph Kern
Ruben L. Bach
Frauke Kreuter
+ Boosted Kernel Weighting – Using Statistical Learning to Improve Inference from Nonprobability Samples 2020 Christoph Kern
Yan Li
Lingxiao Wang
+ Global Trends and Predictors of Face Mask Usage During the COVID-19 Pandemic 2020 Elena Badillo‐Goicoechea
Ting-Hsuan Chang
Esther Kim
Sarah LaRocca
Katherine Morris
Xiaoyi Deng
Samantha Chiu
Adrianne Bradford
Andrés J. Garcı́a
Christoph Kern
+ A longitudinal framework for predicting nonresponse in panel surveys 2019 Christoph Kern
Bernd Weiß
Jan-Philipp Kolb
+ A Longitudinal Framework for Predicting Nonresponse in Panel Surveys 2019 Christoph Kern
Bernd Weiß
Jan-Philipp Kolb
+ Comparing Coefficients of Nonlinear Multivariate Regression Models Between Equations 2015 Christoph Kern
Petra Stein
Common Coauthors
Commonly Cited References
Action Title Year Authors # of times referenced
+ PDF Chat A Survey on Bias and Fairness in Machine Learning 2021 Ninareh Mehrabi
Fred Morstatter
Nripsuta Ani Saxena
Kristina Lerman
Aram Galstyan
6
+ Regression Shrinkage and Selection Via the Lasso 1996 Robert Tibshirani
4
+ PDF Chat Additive logistic regression: a statistical view of boosting (With discussion and a rejoinder by the authors) 2000 Jerome H. Friedman
Trevor Hastie
Robert Tibshirani
4
+ PDF Chat Algorithmic fairness datasets: the story so far 2022 Alessandro Fabris
S. Messina
Gianmaria Silvello
Gian Antonio Susto
4
+ It's COMPASlicated: The Messy Relationship between RAI Datasets and Algorithmic Fairness Benchmarks 2021 Michelle Bao
Angela Zhou
Samantha A. Zottola
Brian Brubach
Sarah L. Desmarais
Aaron Horowitz
Kristian Lum
Suresh Venkatasubramanian
3
+ PDF Chat WEIRD FAccTs: How Western, Educated, Industrialized, Rich, and Democratic is FAccT? 2023 Ali Akbar Septiandri
Marios Constantinides
Mohammad Tahaei
Daniele Quercia
3
+ PDF Chat A comparative study of fairness-enhancing interventions in machine learning 2019 Sorelle A. Friedler
Carlos Scheidegger
Suresh Venkatasubramanian
Sonam Choudhary
Evan P. Hamilton
Derek Roth
3
+ Imputation Rules to Improve the Education Variable in the IAB Employment Subsample 2006 Bernd Fitzenberger
Aderonke Osikominu
Robert Völter
3
+ Scikit-learn: Machine Learning in Python 2012 Fabián Pedregosa
Gaël Varoquaux
Alexandre Gramfort
Vincent Michel
Bertrand Thirion
Olivier Grisel
Mathieu Blondel
Peter Prettenhofer
Ron J. Weiss
Vincent Dubourg
3
+ PDF Chat Fairness through awareness 2012 Cynthia Dwork
Moritz Hardt
Toniann Pitassi
Omer Reingold
Richard S. Zemel
2
+ PDF Chat A survey on datasets for fairness‐aware machine learning 2022 Tai Le Quy
Arjun Roy
Vasileios Iosifidis
Wenbin Zhang
Eirini Ntoutsi
2
+ Retiring Adult: New Datasets for Fair Machine Learning 2021 Frances Ding
Moritz Hardt
John A. Miller
Ludwig Schmidt
2
+ Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition 2022 Rhea Sanjay Sukthanker
Samuel Dooley
John P. Dickerson
Colin White
Frank Hutter
Micah Goldblum
2
+ Inference for Nonprobability Samples 2017 Michael R. Elliott
Richard Valliant
2
+ Multi-Target Multiplicity: Flexibility and Fairness in Target Specification under Resource Constraints 2023 Jamelle Watson-Daniels
Solon Barocas
Jake M. Hofman
Alexandra Chouldechova
2
+ Modeling the Machine Learning Multiverse 2022 Samuel J. Bell
Onno Kampman
Jesse Dodge
Neil D. Lawrence
2
+ PDF Chat The Dataset Multiplicity Problem: How Unreliable Data Impacts Predictions 2023 Anna P. Meyer
Aws Albarghouthi
Loris D’Antoni
2
+ PDF Chat Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges 2023 Bernd Bischl
Martin Binder
Michel Lang
Tobias Pielok
Jakob Richter
Stefan Coors
Janek Thomas
Theresa Ullmann
Marc Becker
Anne‐Laure Boulesteix
2
+ Debiasing classifiers: is reality at variance with expectation? 2020 Ashrya Agrawal
Florian Pfisterer
Bernd Bischl
Francois Buet-Golfouse
Srijan Sood
Jiahao Chen
Sameena Shah
Sebastian J. Vollmer
2
+ Observing many researchers using the same data and hypothesis reveals a hidden universe of uncertainty 2022 Nate Breznau
Eike Mark Rinke
Alexander Wuttke
Hung Hoang Viet Nguyen
Muna Adem
Jule Adriaans
Amalia Álvarez-Benjumea
Henrik Kenneth Andersen
Daniel Auer
Flávio Azevedo
2
+ Fairlearn: Assessing and Improving Fairness of AI Systems 2023 Hilde Weerts
Miroslav Dudı́k
R. J. Edgar
Adrin Jalali
Roman Lutz
Michael P. Madaio
2
+ PDF Chat Arbitrariness and Social Prediction: The Confounding Role of Variance in Fair Classification 2024 A. Feder Cooper
Katherine Lee
Madiha Zahrah Choksi
Solon Barocas
Christopher De
James Grimmelmann
Jon Kleinberg
Siddhartha Sen
Baobao Zhang
2
+ An Introduction to Algorithmic Fairness 2021 Hilde Weerts
2
+ Fair Bayesian Optimization 2021 Valerio Perrone
Michele Donini
Muhammad Bilal Zafar
Robin Schmucker
Krishnaram Kenthapadi
Cédric Archambeau
2
+ An Empirical Study of Rich Subgroup Fairness for Machine Learning 2019 Michael Kearns
Seth Neel
Aaron Roth
Zhiwei Steven Wu
2
+ False-Positive Psychology 2011 Joseph P. Simmons
Leif D. Nelson
Uri Simonsohn
2
+ Equality of Opportunity in Supervised Learning 2016 Moritz Hardt
Eric Price
Nathan Srebro
2
+ Fairness in Algorithmic Profiling: A German Case Study 2021 Christoph Kern
Ruben L. Bach
Hannah Mautner
Frauke Kreuter
2
+ PDF Chat Model-Based Recursive Partitioning 2008 Achim Zeileis
Torsten Hothorn
Kurt Hornik
2
+ Generalized Functional ANOVA Diagnostics for High-Dimensional Functions of Dependent Variables 2007 Giles Hooker
2
+ PDF Chat Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author) 2001 Leo Breiman
1
+ PDF Chat Certifying and Removing Disparate Impact 2015 Michael Feldman
Sorelle A. Friedler
John Moeller
Carlos Scheidegger
Suresh Venkatasubramanian
1
+ Estimating Propensity Adjustments for Volunteer Web Surveys 2011 Richard Valliant
Jill A. Dever
1
+ Courses or individual counselling: does job search assistance work? 2014 Sarah Bernhard
Eva Kopf
1
+ Selection criteria and generalizability within the counterfactual framework: explaining the paradox of antidepressant-induced suicidality? 2009 Herbert I. Weisberg
Vanessa Hayden
Victor P Pontes
1
+ Analysing the probability of attrition in a longitudinal survey 2010 Gabriele B. Durrant
Harvey Goldstein
1
+ PDF Chat Model-based boosting in R: a hands-on tutorial using the R package mboost 2012 Benjamin Hofner
Andreas Mayr
Nikolay Robinzonov
Matthias Schmid
1
+ Stochastic gradient boosting 2002 Jerome H. Friedman
1
+ The Effects of Promised Monetary Incentives on Attrition in a Long-Term Panel Survey 2008 Jay L. Zagorsky
Patricia Rhoton
1
+ Satisficing in surveys: Initial evidence 1996 Jon A. Krosnick
Sowmya Narayan
Wendy R. Smith
1
+ PDF Chat The calibration of treatment effects from clinical trials to target populations 2009 Constantine Frangakis
1
+ PDF Chat Improving propensity score weighting using machine learning 2009 Brian K. Lee
Justin Lessler
Elizabeth A. Stuart
1
+ PDF Chat The Use of Propensity Scores to Assess the Generalizability of Results from Randomized Trials 2010 Elizabeth A. Stuart
Stephen R. Cole
Catherine P. Bradshaw
Philip J. Leaf
1
+ Effects of Monotone and Nonmonotone Attrition on Parameter Estimates in Regression Models with Educational Data: Demographic Effects on Achievement, Aspirations, and Attitudes 1998 David T. Burkam
Valerie E. Lee
1
+ PDF Chat Covariate Balancing Propensity Score 2013 Kosuke Imai
Marc Ratkovic
1
+ Constructing a Control Group Using Multivariate Matched Sampling Methods That Incorporate the Propensity Score 1985 Paul R. Rosenbaum
Donald B. Rubin
1
+ PDF Chat Responsive Design for Household Surveys: Tools for Actively Controlling Survey Errors and Costs 2006 Robert M. Groves
Steven G. Heeringa
1
+ Estimating causal effects of treatments in randomized and nonrandomized studies. 1974 Donald B. Rubin
1
+ Practical Bayesian Optimization of Machine Learning Algorithms 2012 Jasper Snoek
Hugo Larochelle
Ryan P. Adams
1
+ Estimation for Volunteer Panel Web Surveys Using Propensity Score Adjustment and Calibration Adjustment 2009 Sung‐Hee Lee
Richard Valliant
1