DC-Check: A Data-Centric AI checklist to guide the development of reliable machine learning systems

9 November 2022

Papers citing "DC-Check: A Data-Centric AI checklist to guide the development of reliable machine learning systems"

39 / 89 papers shown

Title
Degenerate Feedback Loops in Recommender Systems Ray Jiang Silvia Chiappa Tor Lattimore András Gyorgy Pushmeet Kohli 54 196 0 27 Feb 2019
An introduction to domain adaptation and transfer learning Wouter M. Kouw Marco Loog OOD 45 291 0 31 Dec 2018
Aequitas: A Bias and Fairness Audit Toolkit Pedro Saleiro Benedict Kuester Loren Hinkson J. London Abby Stevens Ari Anisfeld Kit T. Rodolfa Rayid Ghani 117 327 0 14 Nov 2018
Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift Stephan Rabanser Stephan Günnemann Zachary Chase Lipton 68 371 0 29 Oct 2018
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova VLM SSL SSeg 1.8K 95,229 0 11 Oct 2018
Model Cards for Model Reporting Margaret Mitchell Simone Wu Andrew Zaldivar Parker Barnes Lucy Vasserman Ben Hutchinson Elena Spitzer Inioluwa Deborah Raji Timnit Gebru 140 1,908 0 05 Oct 2018
Techniques for Interpretable Machine Learning Mengnan Du Ninghao Liu Helen Zhou FaML 95 1,092 0 31 Jul 2018
Automated Data Slicing for Model Validation:A Big data - AI Integration Approach Yeounoh Chung Tim Kraska N. Polyzotis Ki Hyun Tae Steven Euijong Whang 96 131 0 16 Jul 2018
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks Kimin Lee Kibok Lee Honglak Lee Jinwoo Shin OODD 194 2,063 0 10 Jul 2018
GAIN: Missing Data Imputation using Generative Adversarial Nets Jinsung Yoon James Jordon M. Schaar GAN 68 1,029 0 07 Jun 2018
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels Zhilu Zhang M. Sabuncu NoLa 85 2,615 0 20 May 2018
Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels Bo Han Quanming Yao Xingrui Yu Gang Niu Miao Xu Weihua Hu Ivor Tsang Masashi Sugiyama NoLa 128 2,082 0 18 Apr 2018
Iterative Learning with Open-set Noisy Labels Yisen Wang Weiyang Liu Xingjun Ma James Bailey H. Zha Le Song Shutao Xia NoLa 84 328 0 31 Mar 2018
Datasheets for Datasets Timnit Gebru Jamie Morgenstern Briana Vecchione Jennifer Wortman Vaughan Hanna M. Wallach Hal Daumé Kate Crawford 292 2,201 0 23 Mar 2018
A comparative study of fairness-enhancing interventions in machine learning Sorelle A. Friedler C. Scheidegger Suresh Venkatasubramanian Sonam Choudhary Evan P. Hamilton Derek Roth FaML 109 648 0 13 Feb 2018
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels Lu Jiang Zhengyuan Zhou Thomas Leung Li Li Li Fei-Fei NoLa 131 1,456 0 14 Dec 2017
Data Augmentation Generative Adversarial Networks Antreas Antoniou Amos Storkey Harrison Edwards MedIm GAN 147 1,074 0 12 Nov 2017
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 805 132,725 0 12 Jun 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.1K 22,090 0 22 May 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 362 4,721 0 15 Mar 2017
MoleculeNet: A Benchmark for Molecular Machine Learning Zhenqin Wu Bharath Ramsundar Evan N. Feinberg Joseph Gomes C. Geniesse Aneesh S. Pappu K. Leswing Vijay S. Pande OOD 343 1,838 0 02 Mar 2017
Domain Adaptation for Visual Applications: A Comprehensive Survey G. Csurka OOD 87 507 0 17 Feb 2017
Correlation Alignment for Unsupervised Domain Adaptation Baochen Sun Jiashi Feng Kate Saenko OOD 53 402 0 06 Dec 2016
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 847 5,847 0 05 Dec 2016
Revisiting Classifier Two-Sample Tests David Lopez-Paz Maxime Oquab 189 406 0 20 Oct 2016
Equality of Opportunity in Supervised Learning Moritz Hardt Eric Price Nathan Srebro FaML 236 4,341 0 07 Oct 2016
Data Programming: Creating Large Training Sets, Quickly Alexander Ratner Christopher De Sa Sen Wu Daniel Selsam Christopher Ré 206 718 0 25 May 2016
Interpretable Distribution Features with Maximum Testing Power Wittawat Jitkrittum Z. Szabó Kacper P. Chwialkowski Arthur Gretton 92 135 0 22 May 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 17,071 0 16 Feb 2016
Loss factorization, weakly supervised learning and label noise robustness Giorgio Patrini Frank Nielsen Richard Nock M. Carioni NoLa 183 113 0 08 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.3K 194,510 0 10 Dec 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 869 9,353 0 06 Jun 2015
Domain-Adversarial Training of Neural Networks Yaroslav Ganin E. Ustinova Hana Ajakan Pascal Germain Hugo Larochelle François Laviolette M. Marchand Victor Lempitsky GAN OOD 390 9,524 0 28 May 2015
Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks José Miguel Hernández-Lobato Ryan P. Adams UQCV BDL 142 946 0 18 Feb 2015
Learning Transferable Features with Deep Adaptation Networks Mingsheng Long Yue Cao Jianmin Wang Michael I. Jordan OOD 223 5,215 0 10 Feb 2015
Unsupervised Domain Adaptation by Backpropagation Yaroslav Ganin Victor Lempitsky OOD 247 6,043 0 26 Sep 2014
A Model of Inductive Bias Learning Jonathan Baxter 113 1,217 0 01 Jun 2011
MissForest - nonparametric missing value imputation for mixed-type data D. Stekhoven Peter Buhlmann 240 4,330 0 04 May 2011
A tutorial on conformal prediction Glenn Shafer V. Vovk 456 1,151 0 21 Jun 2007