Characterising Bias in Compressed Models

6 October 2020

Papers citing "Characterising Bias in Compressed Models"

46 / 46 papers shown

Title
Sparse Training from Random Initialization: Aligning Lottery Ticket Masks using Weight Symmetry Mohammed Adnan Rohan Jain Ekansh Sharma Rahul Krishnan Yani Andrew Ioannou 56 0 0 08 May 2025
Fairness of Deep Ensembles: On the interplay between per-group task difficulty and under-representation Estanislao Claucich Sara Hooker Diego H. Milone Enzo Ferrante Rodrigo Echeveste FedML 49 0 0 24 Jan 2025
SWITCH: Studying with Teacher for Knowledge Distillation of Large Language Models Jahyun Koo Yerin Hwang Yongil Kim Taegwan Kang Hyunkyung Bae Kyomin Jung 55 0 0 25 Oct 2024
Compress and Compare: Interactively Evaluating Efficiency and Behavior Across ML Model Compression Experiments Angie Boggust Venkatesh Sivaraman Yannick Assogba Donghao Ren Dominik Moritz Fred Hohman VLM 50 3 0 06 Aug 2024
How Does Quantization Affect Multilingual LLMs? Kelly Marchisio Saurabh Dash Hongyu Chen Dennis Aumiller A. Ustun Sara Hooker Sebastian Ruder MQ 44 6 0 03 Jul 2024
Mind the Graph When Balancing Data for Fairness or Robustness Jessica Schrouff Alexis Bellot Amal Rannen-Triki Alan Malek Isabela Albuquerque A. Gretton Alexander DÁmour Silvia Chiappa OOD CML 38 1 0 25 Jun 2024
Predictive Churn with the Set of Good Models J. Watson-Daniels Flavio du Pin Calmon Alexander DÁmour Carol Xuan Long David C. Parkes Berk Ustun 81 7 0 12 Feb 2024
Is Adversarial Training with Compressed Datasets Effective? Tong Chen Raghavendra Selvan AAML 52 0 0 08 Feb 2024
Report of the DOE/NSF Workshop on Correctness in Scientific Computing, June 2023, Orlando, FL Maya Gokhale Ganesh Gopalakrishnan Jackson Mayo Santosh Nagarakatte Cindy Rubio-González Stephen F. Siegel 39 3 0 25 Dec 2023
Uncovering the Hidden Cost of Model Compression Diganta Misra Muawiz Chaudhary Agam Goyal Bharat Runwal Pin-Yu Chen VLM 30 0 0 29 Aug 2023
Self-Distilled Quantization: Achieving High Compression Rates in Transformer-Based Language Models James OÑeill Sourav Dutta VLM MQ 32 1 0 12 Jul 2023
On The Impact of Machine Learning Randomness on Group Fairness Prakhar Ganesh Hong Chang Martin Strobel Reza Shokri FaML 21 30 0 09 Jul 2023
Cross-lingual Transfer Can Worsen Bias in Sentiment Analysis Seraphina Goldfarb-Tarrant Bjorn Ross Adam Lopez 31 7 0 22 May 2023
A Comprehensive Study on Dataset Distillation: Performance, Privacy, Robustness and Fairness Zongxiong Chen Jiahui Geng Derui Zhu Herbert Woisetschlaeger Qing Li Sonja Schimmler Ruben Mayer Chunming Rong DD 24 9 0 05 May 2023
Angler: Helping Machine Translation Practitioners Prioritize Model Improvements Samantha Robertson Zijie J. Wang Dominik Moritz Mary Beth Kery Fred Hohman 30 15 0 12 Apr 2023
Do We Train on Test Data? The Impact of Near-Duplicates on License Plate Recognition Rayson Laroca Valter Estevam A. Britto Rodrigo Minetto David Menotti 26 10 0 10 Apr 2023
Counting Carbon: A Survey of Factors Influencing the Emissions of Machine Learning A. Luccioni Alex Hernandez-Garcia 24 45 0 16 Feb 2023
Getting Away with More Network Pruning: From Sparsity to Geometry and Linear Regions Junyang Cai Khai-Nguyen Nguyen Nishant Shrestha Aidan Good Ruisen Tu Xin Yu Shandian Zhe Thiago Serra MLT 32 7 0 19 Jan 2023
Fairness Increases Adversarial Vulnerability Cuong Tran Keyu Zhu Ferdinando Fioretto Pascal Van Hentenryck 20 6 0 21 Nov 2022
A Fair Loss Function for Network Pruning Robbie Meyer Alexander Wong CVBM 19 3 0 18 Nov 2022
Metadata Archaeology: Unearthing Data Subsets by Leveraging Training Dynamics Shoaib Ahmed Siddiqui Nitarshan Rajkumar Tegan Maharaj David M. Krueger Sara Hooker 37 27 0 20 Sep 2022
Efficient Methods for Natural Language Processing: A Survey Marcos Vinícius Treviso Ji-Ung Lee Tianchu Ji Betty van Aken Qingqing Cao ... Emma Strubell Niranjan Balasubramanian Leon Derczynski Iryna Gurevych Roy Schwartz 28 109 0 31 Aug 2022
FairGRAPE: Fairness-aware GRAdient Pruning mEthod for Face Attribute Classification Xiao-Ze Lin Seungbae Kim Jungseock Joo CVBM 29 38 0 22 Jul 2022
Recall Distortion in Neural Network Pruning and the Undecayed Pruning Algorithm Aidan Good Jia-Huei Lin Hannah Sieg Mikey Ferguson Xin Yu Shandian Zhe J. Wieczorek Thiago Serra 23 11 0 07 Jun 2022
Towards Fair Federated Recommendation Learning: Characterizing the Inter-Dependence of System and Data Heterogeneity Kiwan Maeng Haiyu Lu Luca Melis John Nguyen Michael G. Rabbat Carole-Jean Wu FedML 29 31 0 30 May 2022
Pruning has a disparate impact on model accuracy Cuong Tran Ferdinando Fioretto Jung-Eun Kim Rakshit Naidu 34 38 0 26 May 2022
What Do Compressed Multilingual Machine Translation Models Forget? Alireza Mohammadshahi Vassilina Nikoulina Alexandre Berard Caroline Brun James Henderson Laurent Besacier AI4CE 40 9 0 22 May 2022
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations Aparna Balagopalan Haoran Zhang Kimia Hamidieh Thomas Hartvigsen Frank Rudzicz Marzyeh Ghassemi 35 77 0 06 May 2022
OccamNets: Mitigating Dataset Bias by Favoring Simpler Hypotheses Robik Shrestha Kushal Kafle Christopher Kanan CML 25 13 0 05 Apr 2022
The Combinatorial Brain Surgeon: Pruning Weights That Cancel One Another in Neural Networks Xin Yu Thiago Serra Srikumar Ramalingam Shandian Zhe 34 48 0 09 Mar 2022
Membership Inference Attacks and Defenses in Neural Network Pruning Xiaoyong Yuan Lan Zhang AAML 10 44 0 07 Feb 2022
Bias in Automated Speaker Recognition Wiebke Toussaint Aaron Yi Ding CVBM 27 44 0 24 Jan 2022
Can Model Compression Improve NLP Fairness Guangxuan Xu Qingyuan Hu 23 26 0 21 Jan 2022
The Effect of Model Compression on Fairness in Facial Expression Recognition Samuil Stoychev Hatice Gunes CVBM 17 19 0 05 Jan 2022
How Well Do Sparse Imagenet Models Transfer? Eugenia Iofinova Alexandra Peste Mark Kurtz Dan Alistarh 19 38 0 26 Nov 2021
LMdiff: A Visual Diff Tool to Compare Language Models Hendrik Strobelt Benjamin Hoover Arvind Satyanarayan Sebastian Gehrmann VLM 29 19 0 02 Nov 2021
On the Current and Emerging Challenges of Developing Fair and Ethical AI Solutions in Financial Services Eren Kurshan Jiahao Chen Victor Storchan Hongda Shen FaML AIFin 24 9 0 02 Nov 2021
NxMTransformer: Semi-Structured Sparsification for Natural Language Understanding via ADMM Connor Holmes Minjia Zhang Yuxiong He Bo Wu 29 18 0 28 Oct 2021
Avoiding Inference Heuristics in Few-shot Prompt-based Finetuning Prasetya Ajie Utama N. Moosavi Victor Sanh Iryna Gurevych AAML 56 35 0 09 Sep 2021
Randomness In Neural Network Training: Characterizing The Impact of Tooling Donglin Zhuang Xingyao Zhang S. Song Sara Hooker 22 75 0 22 Jun 2021
Deep Learning Through the Lens of Example Difficulty R. Baldock Hartmut Maennel Behnam Neyshabur 19 155 0 17 Jun 2021
Efficient Deep Learning: A Survey on Making Deep Learning Models Smaller, Faster, and Better Gaurav Menghani VLM MedIm 23 365 0 16 Jun 2021
Can Subnetwork Structure be the Key to Out-of-Distribution Generalization? Dinghuai Zhang Kartik Ahuja Yilun Xu Yisen Wang Aaron Courville OOD 20 95 0 05 Jun 2021
An Information-Theoretic Justification for Model Pruning Berivan Isik Tsachy Weissman Albert No 84 35 0 16 Feb 2021
Estimating Example Difficulty Using Variance of Gradients Chirag Agarwal Daniel D'souza Sara Hooker 208 107 0 26 Aug 2020
What is the State of Neural Network Pruning? Davis W. Blalock Jose Javier Gonzalez Ortiz Jonathan Frankle John Guttag 185 1,027 0 06 Mar 2020