Timezone: »
Learning-from-crowds aims to design proper aggregation strategies to infer the unknown true labels from the noisy labels provided by ordinary web workers. This paper presents max-margin majority voting (M^3V) to improve the discriminative ability of majority voting and further presents a Bayesian generalization to incorporate the flexibility of generative methods on modeling noisy observations with worker confusion matrices. We formulate the joint learning as a regularized Bayesian inference problem, where the posterior regularization is derived by maximizing the margin between the aggregated score of a potential true label and that of any alternative label. Our Bayesian model naturally covers the Dawid-Skene estimator and M^3V. Empirical results demonstrate that our methods are competitive, often achieving better results than state-of-the-art estimators.
Author Information
TIAN TIAN (Tsinghua University)
Jun Zhu (Tsinghua University)
More from the Same Authors
-
2021 : Counter-Strike Deathmatch with Large-Scale Behavioural Cloning »
Tim Pearce · Jun Zhu -
2022 Poster: A Unified Hard-Constraint Framework for Solving Geometrically Complex PDEs »
Songming Liu · Hao Zhongkai · Chengyang Ying · Hang Su · Jun Zhu · Ze Cheng -
2022 Poster: Isometric 3D Adversarial Examples in the Physical World »
Yibo Miao · Yinpeng Dong · Jun Zhu · Xiao-Shan Gao -
2022 Poster: Confidence-based Reliable Learning under Dual Noises »
Peng Cui · Yang Yue · Zhijie Deng · Jun Zhu -
2022 Poster: EGSDE: Unpaired Image-to-Image Translation via Energy-Guided Stochastic Differential Equations »
Min Zhao · Fan Bao · Chongxuan LI · Jun Zhu -
2022 Poster: ViewFool: Evaluating the Robustness of Visual Recognition to Adversarial Viewpoints »
Yinpeng Dong · Shouwei Ruan · Hang Su · Caixin Kang · Xingxing Wei · Jun Zhu -
2022 Poster: DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps »
Cheng Lu · Yuhao Zhou · Fan Bao · Jianfei Chen · Chongxuan LI · Jun Zhu -
2022 Poster: Accelerated Linearized Laplace Approximation for Bayesian Deep Learning »
Zhijie Deng · Feng Zhou · Jun Zhu -
2022 : Physics-Guided Discovery of Highly Nonlinear Parametric Partial Differential Equations »
Yingtao Luo · Qiang Liu · Yuntian Chen · Wenbo Hu · TIAN TIAN · Jun Zhu -
2022 : All are Worth Words: a ViT Backbone for Score-based Diffusion Models »
Fan Bao · Chongxuan LI · Yue Cao · Jun Zhu -
2022 : Why Are Conditional Generative Models Better Than Unconditional Ones? »
Fan Bao · Chongxuan LI · Jiacheng Sun · Jun Zhu -
2022 : On Equivalences between Weight and Function-Space Langevin Dynamics »
Ziyu Wang · Yuhao Zhou · Ruqi Zhang · Jun Zhu -
2022 Spotlight: Lightning Talks 6A-2 »
Yichuan Mo · Botao Yu · Gang Li · Zezhong Xu · Haoran Wei · Arsene Fansi Tchango · Raef Bassily · Haoyu Lu · Qi Zhang · Songming Liu · Mingyu Ding · Peiling Lu · Yifei Wang · Xiang Li · Dongxian Wu · Ping Guo · Wen Zhang · Hao Zhongkai · Mehryar Mohri · Rishab Goel · Yisen Wang · Yifei Wang · Yangguang Zhu · Zhi Wen · Ananda Theertha Suresh · Chengyang Ying · Yujie Wang · Peng Ye · Rui Wang · Nanyi Fei · Hui Chen · Yiwen Guo · Wei Hu · Chenglong Liu · Julien Martel · Yuqi Huo · Wu Yichao · Hang Su · Yisen Wang · Peng Wang · Huajun Chen · Xu Tan · Jun Zhu · Ding Liang · Zhiwu Lu · Joumana Ghosn · Shanshan Zhang · Wei Ye · Ze Cheng · Shikun Zhang · Tao Qin · Tie-Yan Liu -
2022 Spotlight: A Unified Hard-Constraint Framework for Solving Geometrically Complex PDEs »
Songming Liu · Hao Zhongkai · Chengyang Ying · Hang Su · Jun Zhu · Ze Cheng -
2022 Spotlight: EGSDE: Unpaired Image-to-Image Translation via Energy-Guided Stochastic Differential Equations »
Min Zhao · Fan Bao · Chongxuan LI · Jun Zhu -
2022 Spotlight: Accelerated Linearized Laplace Approximation for Bayesian Deep Learning »
Zhijie Deng · Feng Zhou · Jun Zhu -
2022 Spotlight: DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps »
Cheng Lu · Yuhao Zhou · Fan Bao · Jianfei Chen · Chongxuan LI · Jun Zhu -
2022 Spotlight: Lightning Talks 4B-1 »
Alexandra Senderovich · Zhijie Deng · Navid Ansari · Xuefei Ning · Yasmin Salehi · Xiang Huang · Chenyang Wu · Kelsey Allen · Jiaqi Han · Nikita Balagansky · Tatiana Lopez-Guevara · Tianci Li · Zhanhong Ye · Zixuan Zhou · Feng Zhou · Ekaterina Bulatova · Daniil Gavrilov · Wenbing Huang · Dennis Giannacopoulos · Hans-peter Seidel · Anton Obukhov · Kimberly Stachenfeld · Hongsheng Liu · Jun Zhu · Junbo Zhao · Hengbo Ma · Nima Vahidi Ferdowsi · Zongzhang Zhang · Vahid Babaei · Jiachen Li · Alvaro Sanchez Gonzalez · Yang Yu · Shi Ji · Maxim Rakhuba · Tianchen Zhao · Yiping Deng · Peter Battaglia · Josh Tenenbaum · Zidong Wang · Chuang Gan · Changcheng Tang · Jessica Hamrick · Kang Yang · Tobias Pfaff · Yang Li · Shuang Liang · Min Wang · Huazhong Yang · Haotian CHU · Yu Wang · Fan Yu · Bei Hua · Lei Chen · Bin Dong -
2022 Spotlight: Lightning Talks 3B-2 »
Yu Huang · Tero Karras · Maxim Kodryan · Shiau Hong Lim · Shudong Huang · Ziyu Wang · Siqiao Xue · ILYAS MALIK · Ekaterina Lobacheva · Miika Aittala · Hongjie Wu · Yuhao Zhou · Yingbin Liang · Xiaoming Shi · Jun Zhu · Maksim Nakhodnov · Timo Aila · Yazhou Ren · James Zhang · Longbo Huang · Dmitry Vetrov · Ivor Tsang · Hongyuan Mei · Samuli Laine · Zenglin Xu · Wentao Feng · Jiancheng Lv -
2022 Spotlight: Fast Instrument Learning with Faster Rates »
Ziyu Wang · Yuhao Zhou · Jun Zhu -
2022 Poster: Fast Instrument Learning with Faster Rates »
Ziyu Wang · Yuhao Zhou · Jun Zhu -
2022 Poster: Censored Quantile Regression Neural Networks for Distribution-Free Survival Analysis »
Tim Pearce · Jong-Hyeon Jeong · yichen jia · Jun Zhu -
2021 Poster: Stability and Generalization of Bilevel Programming in Hyperparameter Optimization »
Fan Bao · Guoqiang Wu · Chongxuan LI · Jun Zhu · Bo Zhang -
2021 Poster: On the Convergence of Prior-Guided Zeroth-Order Optimization Algorithms »
Shuyu Cheng · Guoqiang Wu · Jun Zhu -
2021 Poster: Scalable Quasi-Bayesian Inference for Instrumental Variable Regression »
Ziyu Wang · Yuhao Zhou · Tongzheng Ren · Jun Zhu -
2021 Poster: Rethinking and Reweighting the Univariate Losses for Multi-Label Ranking: Consistency and Generalization »
Guoqiang Wu · Chongxuan LI · Kun Xu · Jun Zhu -
2021 Poster: AFEC: Active Forgetting of Negative Transfer in Continual Learning »
Liyuan Wang · Mingtian Zhang · Zhongfan Jia · Qian Li · Chenglong Bao · Kaisheng Ma · Jun Zhu · Yi Zhong -
2021 Poster: Accumulative Poisoning Attacks on Real-time Data »
Tianyu Pang · Xiao Yang · Yinpeng Dong · Hang Su · Jun Zhu -
2020 Poster: Multi-label classification: do Hamming loss and subset accuracy really conflict with each other? »
Guoqiang Wu · Jun Zhu -
2020 Poster: Bi-level Score Matching for Learning Energy-based Latent Variable Models »
Fan Bao · Chongxuan LI · Kun Xu · Hang Su · Jun Zhu · Bo Zhang -
2020 Poster: Further Analysis of Outlier Detection with Deep Generative Models »
Ziyu Wang · Bin Dai · David P Wipf · Jun Zhu -
2020 Poster: Efficient Learning of Generative Models via Finite-Difference Score Matching »
Tianyu Pang · Kun Xu · Chongxuan LI · Yang Song · Stefano Ermon · Jun Zhu -
2020 Poster: Calibrated Reliable Regression using Maximum Mean Discrepancy »
Peng Cui · Wenbo Hu · Jun Zhu -
2020 Poster: Boosting Adversarial Training with Hypersphere Embedding »
Tianyu Pang · Xiao Yang · Yinpeng Dong · Kun Xu · Jun Zhu · Hang Su -
2020 Poster: Adversarial Distributional Training for Robust Deep Learning »
Yinpeng Dong · Zhijie Deng · Tianyu Pang · Jun Zhu · Hang Su -
2020 Poster: Understanding and Exploring the Network with Stochastic Architectures »
Zhijie Deng · Yinpeng Dong · Shifeng Zhang · Jun Zhu -
2019 Poster: Improving Black-box Adversarial Attacks with a Transfer-based Prior »
Shuyu Cheng · Yinpeng Dong · Tianyu Pang · Hang Su · Jun Zhu -
2019 Poster: Generative Well-intentioned Networks »
Justin Cosentino · Jun Zhu -
2019 Poster: Multi-objects Generation with Amortized Structural Regularization »
Kun Xu · Chongxuan LI · Jun Zhu · Bo Zhang -
2018 Poster: Semi-crowdsourced Clustering with Deep Generative Models »
Yucen Luo · TIAN TIAN · Jiaxin Shi · Jun Zhu · Bo Zhang -
2018 Poster: Towards Robust Detection of Adversarial Examples »
Tianyu Pang · Chao Du · Yinpeng Dong · Jun Zhu -
2018 Spotlight: Towards Robust Detection of Adversarial Examples »
Tianyu Pang · Chao Du · Yinpeng Dong · Jun Zhu -
2018 Poster: Graphical Generative Adversarial Networks »
Chongxuan LI · Max Welling · Jun Zhu · Bo Zhang -
2017 Poster: Triple Generative Adversarial Nets »
Chongxuan LI · Kun Xu · Jun Zhu · Bo Zhang -
2017 Poster: Population Matching Discrepancy and Applications in Deep Learning »
Jianfei Chen · Chongxuan LI · Yizhong Ru · Jun Zhu -
2016 Poster: Kernel Bayesian Inference with Posterior Regularization »
Yang Song · Jun Zhu · Yong Ren -
2016 Poster: Stochastic Gradient Geodesic MCMC Methods »
Chang Liu · Jun Zhu · Yang Song -
2016 Poster: Conditional Generative Moment-Matching Networks »
Yong Ren · Jun Zhu · Jialian Li · Yucen Luo -
2015 Poster: Max-Margin Deep Generative Models »
Chongxuan Li · Jun Zhu · Tim Shi · Bo Zhang -
2014 Poster: Distributed Bayesian Posterior Sampling via Moment Sharing »
Minjie Xu · Balaji Lakshminarayanan · Yee Whye Teh · Jun Zhu · Bo Zhang -
2014 Poster: Spectral Methods for Supervised Topic Models »
Yining Wang · Jun Zhu -
2014 Poster: Robust Bayesian Max-Margin Clustering »
Changyou Chen · Jun Zhu · Xinhua Zhang -
2013 Poster: Scalable Inference for Logistic-Normal Topic Models »
Jianfei Chen · Jun Zhu · Zi Wang · Xun Zheng · Bo Zhang -
2012 Poster: Monte Carlo Methods for Maximum Margin Supervised Topic Models »
Qixia Jiang · Jun Zhu · Maosong Sun · Eric Xing -
2012 Poster: Bayesian Nonparametric Maximum Margin Matrix Factorization for Collaborative Prediction »
Minjie Xu · Jun Zhu · Bo Zhang -
2011 Poster: Infinite Latent SVM for Classification and Multi-task Learning »
Jun Zhu · Ning Chen · Eric Xing -
2010 Poster: Large Margin Learning of Upstream Scene Understanding Models »
Jun Zhu · Li-Jia Li · Li Fei-Fei · Eric Xing -
2010 Poster: Predictive Subspace Learning for Multi-view Data: a Large Margin Approach »
Ning Chen · Jun Zhu · Eric Xing -
2010 Poster: Adaptive Multi-Task Lasso: with Application to eQTL Detection »
Seunghak Lee · Jun Zhu · Eric Xing -
2010 Poster: Efficient Relational Learning with Hidden Variable Detection »
Ni Lao · Jun Zhu · Liu Xinwang · Yandong Liu · William Cohen -
2008 Poster: Partially Observed Maximum Entropy Discrimination Markov Networks »
Jun Zhu · Eric Xing · Bo Zhang