Timezone: »
Despite a surge of recent advances in promoting machine Learning (ML) fairness, the existing mainstream approaches mostly require training or finetuning the entire weights of the neural network to meet the fairness criteria. However, this is often infeasible in practice for those large-scale trained models due to large computational and storage costs, low data efficiency, and model privacy issues. In this paper, we propose a new generic fairness learning paradigm, called FairReprogram, which incorporates the model reprogramming technique. Specifically, FairReprogram considers the case where models can not be changed and appends to the input a set of perturbations, called the fairness trigger, which is tuned towards the fairness criteria under a min-max formulation. We further introduce an information-theoretic framework that explains why and under what conditions fairness goals can be achieved using the fairness trigger. We show both theoretically and empirically that the fairness trigger can effectively obscure demographic biases in the output prediction of fixed ML models by providing false demographic information that hinders the model from utilizing the correct demographic information to make the prediction. Extensive experiments on both NLP and CV datasets demonstrate that our method can achieve better fairness improvements than retraining-based methods with far less data dependency under two widely-used fairness criteria. Codes are available at https://github.com/UCSB-NLP-Chang/Fairness-Reprogramming.git.
Author Information
Guanhua Zhang (University of California, Santa Barbara)
Yihua Zhang (Michigan State University)
Yang Zhang (MIT-IBM Watson AI Lab)
Wenqi Fan (The Hong Kong Polytechnic University)
Qing Li (City University of Hong Kong)
Sijia Liu (Michigan State University)
Shiyu Chang (UC Santa Barbara)
More from the Same Authors
-
2021 Spotlight: MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge »
Geng Yuan · Xiaolong Ma · Wei Niu · Zhengang Li · Zhenglun Kong · Ning Liu · Yifan Gong · Zheng Zhan · Chaoyang He · Qing Jin · Siyue Wang · Minghai Qin · Bin Ren · Yanzhi Wang · Sijia Liu · Xue Lin -
2021 Spotlight: PARP: Prune, Adjust and Re-Prune for Self-Supervised Speech Recognition »
Cheng-I Jeff Lai · Yang Zhang · Alexander Liu · Shiyu Chang · Yi-Lun Liao · Yung-Sung Chuang · Kaizhi Qian · Sameer Khurana · David Cox · Jim Glass -
2021 : Sign-MAML: Efficient Model-Agnostic Meta-Learning by SignSGD »
Chen Fan · Parikshit Ram · Sijia Liu -
2022 : On the Robustness of deep learning-based MRI Reconstruction to image transformations »
jinghan jia · Mingyi Hong · Yimeng Zhang · Mehmet Akcakaya · Sijia Liu -
2022 : Visual Prompting for Adversarial Robustness »
Aochuan Chen · Peter Lorenz · Yuguang Yao · Pin-Yu Chen · Sijia Liu -
2022 : Visual Prompting for Adversarial Robustness »
Aochuan Chen · Peter Lorenz · Yuguang Yao · Pin-Yu Chen · Sijia Liu -
2023 : AutoVP: An Automated Visual Prompting Framework and Benchmark »
Hsi-Ai Tsao · Lei Hsiung · Pin-Yu Chen · Sijia Liu · Tsung-Yi Ho -
2023 : AutoVP: An Automated Visual Prompting Framework and Benchmark »
Hsi-Ai Tsao · Lei Hsiung · Pin-Yu Chen · Sijia Liu · Tsung-Yi Ho -
2023 : Exploring the Potential of Large Language Models (LLMs) in Learning on Graph »
Zhikai Chen · Haitao Mao · Hang Li · Wei Jin · Hongzhi Wen · Xiaochi Wei · Shuaiqiang Wang · Dawei Yin · Wenqi Fan · Hui Liu · Jiliang Tang -
2023 : What Improves the Generalization of Graph Transformer? A Theoretical Dive into Self-attention and Positional Encoding »
Hongkang Li · Meng Wang · Tengfei Ma · Sijia Liu · ZAIXI ZHANG · Pin-Yu Chen -
2023 : From Trojan Horses to Castle Walls: Unveiling Bilateral Backdoor Effects in Diffusion Models »
Zhuoshi Pan · Yuguang Yao · Gaowen Liu · Bingquan Shen · H. Vicky Zhao · Ramana Kompella · Sijia Liu -
2023 Poster: Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer Learning »
Yihua Zhang · Yimeng Zhang · Aochuan Chen · jinghan jia · Jiancheng Liu · Gaowen Liu · Mingyi Hong · Shiyu Chang · Sijia Liu -
2023 Poster: SheetCopilot: Bringing Software Productivity to the Next Level through Large Language Models »
Hongxin Li · Jingran Su · Yuntao Chen · Qing Li · ZHAO-XIANG ZHANG -
2023 Poster: On the Convergence and Sample Complexity Analysis of Deep Q-Networks with $\epsilon$-Greedy Exploration »
Shuai Zhang · Hongkang Li · Meng Wang · Miao Liu · Pin-Yu Chen · Songtao Lu · Sijia Liu · Keerthiram Murugesan · Subhajit Chaudhury -
2023 Poster: Model Sparsity Can Simplify Machine Unlearning »
jinghan jia · Jiancheng Liu · Parikshit Ram · Yuguang Yao · Gaowen Liu · Yang Liu · PRANAY SHARMA · Sijia Liu -
2022 : Q & A »
Sayak Paul · Sijia Liu · Pin-Yu Chen -
2022 : Deep dive on foundation models for code »
Sijia Liu -
2022 Tutorial: Foundational Robustness of Foundation Models »
Pin-Yu Chen · Sijia Liu · Sayak Paul -
2022 : Basics in foundation model and robustness »
Pin-Yu Chen · Sijia Liu -
2022 Poster: Losses Can Be Blessings: Routing Self-Supervised Speech Representations Towards Efficient Multilingual and Multitask Speech Processing »
Yonggan Fu · Yang Zhang · Kaizhi Qian · Zhifan Ye · Zhongzhi Yu · Cheng-I Jeff Lai · Celine Lin -
2022 Poster: Advancing Model Pruning via Bi-level Optimization »
Yihua Zhang · Yuguang Yao · Parikshit Ram · Pu Zhao · Tianlong Chen · Mingyi Hong · Yanzhi Wang · Sijia Liu -
2021 Poster: Understanding Interlocking Dynamics of Cooperative Rationalization »
Mo Yu · Yang Zhang · Shiyu Chang · Tommi Jaakkola -
2021 Poster: Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Sparse Neural Networks »
Shuai Zhang · Meng Wang · Sijia Liu · Pin-Yu Chen · Jinjun Xiong -
2021 Poster: Adversarial Attack Generation Empowered by Min-Max Optimization »
Jingkang Wang · Tianyun Zhang · Sijia Liu · Pin-Yu Chen · Jiacen Xu · Makan Fardad · Bo Li -
2021 Poster: TransGAN: Two Pure Transformers Can Make One Strong GAN, and That Can Scale Up »
Yifan Jiang · Shiyu Chang · Zhangyang Wang -
2021 Poster: Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks »
Yonggan Fu · Qixuan Yu · Yang Zhang · Shang Wu · Xu Ouyang · David Cox · Yingyan Lin -
2021 Poster: Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot? »
Xiaolong Ma · Geng Yuan · Xuan Shen · Tianlong Chen · Xuxi Chen · Xiaohan Chen · Ning Liu · Minghai Qin · Sijia Liu · Zhangyang Wang · Yanzhi Wang -
2021 Poster: When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning? »
Lijie Fan · Sijia Liu · Pin-Yu Chen · Gaoyuan Zhang · Chuang Gan -
2021 Poster: MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge »
Geng Yuan · Xiaolong Ma · Wei Niu · Zhengang Li · Zhenglun Kong · Ning Liu · Yifan Gong · Zheng Zhan · Chaoyang He · Qing Jin · Siyue Wang · Minghai Qin · Bin Ren · Yanzhi Wang · Sijia Liu · Xue Lin -
2021 Poster: PARP: Prune, Adjust and Re-Prune for Self-Supervised Speech Recognition »
Cheng-I Jeff Lai · Yang Zhang · Alexander Liu · Shiyu Chang · Yi-Lun Liao · Yung-Sung Chuang · Kaizhi Qian · Sameer Khurana · David Cox · Jim Glass -
2020 Poster: Training Stronger Baselines for Learning to Optimize »
Tianlong Chen · Weiyi Zhang · Zhou Jingyang · Shiyu Chang · Sijia Liu · Lisa Amini · Zhangyang "Atlas" Wang -
2020 Spotlight: Training Stronger Baselines for Learning to Optimize »
Tianlong Chen · Weiyi Zhang · Zhou Jingyang · Shiyu Chang · Sijia Liu · Lisa Amini · Zhangyang "Atlas" Wang -
2020 Poster: Higher-Order Certification For Randomized Smoothing »
Jeet Mohapatra · Ching-Yun Ko · Tsui-Wei Weng · Pin-Yu Chen · Sijia Liu · Luca Daniel -
2020 Poster: The Lottery Ticket Hypothesis for Pre-trained BERT Networks »
Tianlong Chen · Jonathan Frankle · Shiyu Chang · Sijia Liu · Yang Zhang · Zhangyang "Atlas" Wang · Michael Carbin -
2020 Spotlight: Higher-Order Certification For Randomized Smoothing »
Jeet Mohapatra · Ching-Yun Ko · Tsui-Wei Weng · Pin-Yu Chen · Sijia Liu · Luca Daniel -
2019 Poster: Tight Certificates of Adversarial Robustness for Randomly Smoothed Classifiers »
Guang-He Lee · Yang Yuan · Shiyu Chang · Tommi Jaakkola -
2019 Poster: A Game Theoretic Approach to Class-wise Selective Rationalization »
Shiyu Chang · Yang Zhang · Mo Yu · Tommi Jaakkola -
2018 Poster: Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization »
Sijia Liu · Bhavya Kailkhura · Pin-Yu Chen · Paishun Ting · Shiyu Chang · Lisa Amini -
2017 Poster: Dilated Recurrent Neural Networks »
Shiyu Chang · Yang Zhang · Wei Han · Mo Yu · Xiaoxiao Guo · Wei Tan · Xiaodong Cui · Michael Witbrock · Mark Hasegawa-Johnson · Thomas Huang