From Social to Individuals: A Parsimonious Path of Multi-Level Models for Crowdsourced Preference Aggregation
暂无分享,去创建一个
Qingming Huang | Xiaochun Cao | Qianqian Xu | Jiechao Xiong | Yuan Yao | Xiaochun Cao | Qingming Huang | Yuan Yao | Qianqian Xu | Jiechao Xiong
[1] Wotao Yin,et al. An Iterative Regularization Method for Total Variation-Based Image Restoration , 2005, Multiscale Model. Simul..
[2] Gerardo Hermosillo,et al. Supervised learning from multiple experts: whom to trust when everyone lies a bit , 2009, ICML '09.
[3] Javier R. Movellan,et al. Whose Vote Should Count More: Optimal Integration of Labels from Labelers of Unknown Expertise , 2009, NIPS.
[4] Eric Horvitz,et al. Identifying and Accounting for Task-Dependent Bias in Crowdsourcing , 2015, HCOMP.
[5] Thorsten Joachims,et al. Optimizing search engines using clickthrough data , 2002, KDD.
[6] J. Friedman. Greedy function approximation: A gradient boosting machine. , 2001 .
[7] Yu Lu,et al. Individualized rank aggregation using nuclear norm regularization , 2014, 2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton).
[8] Guoliang Li,et al. Truth Inference in Crowdsourcing: Is the Problem Solved? , 2017, Proc. VLDB Endow..
[9] Jian Li,et al. CDB: Optimizing Queries with Crowd-Based Selections and Joins , 2017, SIGMOD Conference.
[10] J. Marsden,et al. A mathematical introduction to fluid mechanics , 1979 .
[11] Arun Rajkumar,et al. A Statistical Convergence Perspective of Algorithms for Rank Aggregation from Pairwise Data , 2014, ICML.
[12] Sergey Brin,et al. The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.
[13] Guoliang Li,et al. Crowdsourced Data Management: A Survey , 2016, IEEE Transactions on Knowledge and Data Engineering.
[14] Ngoc Mai Tran,et al. HodgeRank Is the Limit of Perron Rank , 2012, Math. Oper. Res..
[15] Aichi Chien,et al. An L1-based variational model for Retinex theory and its application to medical images , 2011, CVPR 2011.
[16] Xiaochun Cao,et al. Parsimonious Mixed-Effects HodgeRank for Crowdsourced Preference Aggregation , 2016, ACM Multimedia.
[17] Tao Xiang,et al. Robust Subjective Visual Property Prediction from Crowdsourced Pairwise Labels , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[18] Milad Shokouhi,et al. Community-based bayesian aggregation models for crowdsourcing , 2014, WWW.
[19] Eero P. Simoncelli,et al. Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.
[20] Qingming Huang,et al. HodgeRank on Random Graphs for Subjective Video Quality Assessment , 2012, IEEE Transactions on Multimedia.
[21] Yuan Yao,et al. Statistical ranking and combinatorial Hodge theory , 2008, Math. Program..
[22] S. Osher,et al. Sparse Recovery via Differential Inclusions , 2014, 1406.7728.
[23] K. Arrow. Social Choice and Individual Values , 1951 .
[24] Stanley Osher,et al. Enhanced statistical rankings via targeted data collection , 2013, ICML.
[25] Guoliang Li,et al. Crowdsourced Data Management: Overview and Challenges , 2017, SIGMOD Conference.
[26] Reynold Cheng,et al. On Optimality of Jury Selection in Crowdsourcing , 2015, EDBT.
[27] Ran Gilad-Bachrach,et al. DART: Dropouts meet Multiple Additive Regression Trees , 2015, AISTATS.
[28] Matthew Lease,et al. SQUARE: A Benchmark for Research on Computing Crowd Consensus , 2013, HCOMP.
[29] Beng Chin Ooi,et al. CDAS: A Crowdsourcing Data Analytics System , 2012, Proc. VLDB Endow..
[30] Vincent Y. F. Tan,et al. Adversarial Top- $K$ Ranking , 2016, IEEE Transactions on Information Theory.
[31] Devavrat Shah,et al. A Data-Driven Approach to Modeling Choice , 2009, NIPS.
[32] Yuan Yao,et al. Analysis of Crowdsourced Sampling Strategies for HodgeRank with Sparse Random Graphs , 2015, Applied and Computational Harmonic Analysis.
[33] Jinfeng Yi,et al. Inferring Users' Preferences from Crowdsourced Pairwise Comparisons: A Matrix Completion Approach , 2013, HCOMP.
[34] Reynold Cheng,et al. DOCS: a domain-aware crowdsourcing system using knowledge bases , 2016, VLDB 2016.
[35] P.-C.-F. Daunou,et al. Mémoire sur les élections au scrutin , 1803 .
[36] Zhifeng Bao,et al. Crowdsourced POI labelling: Location-aware result inference and Task Assignment , 2016, 2016 IEEE 32nd International Conference on Data Engineering (ICDE).
[37] S. Osher,et al. Statistical ranking using the $l^{1}$-norm on graphs , 2013 .
[38] Yoram Singer,et al. An Efficient Boosting Algorithm for Combining Preferences by , 2013 .
[39] Ralph L. Day,et al. Position Bias in Paired Product Tests , 1969 .
[40] Stella Yu,et al. Angular Embedding: A Robust Quadratic Criterion , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[41] Asuman E. Ozdaglar,et al. Flows and Decompositions of Games: Harmonic and Potential Games , 2010, Math. Oper. Res..
[42] Guoliang Li,et al. DOCS: Domain-Aware Crowdsourcing System , 2016, Proc. VLDB Endow..
[43] Philip D. Plowright,et al. Convexity , 2019, Optimization for Chemical and Biochemical Engineering.
[44] Devavrat Shah,et al. Learning Mixed Multinomial Logit Model from Ordinal Data , 2014, NIPS.
[45] Moni Naor,et al. Rank aggregation methods for the Web , 2001, WWW '01.
[46] Michael I. Jordan,et al. Convexity, Classification, and Risk Bounds , 2006 .
[47] Jing Yuan,et al. Convex Hodge Decomposition and Regularization of Image Flows , 2009, Journal of Mathematical Imaging and Vision.
[48] Nathan Srebro,et al. Fast maximum margin matrix factorization for collaborative prediction , 2005, ICML.
[49] Ruslan Salakhutdinov,et al. Bayesian probabilistic matrix factorization using Markov chain Monte Carlo , 2008, ICML '08.
[50] A. P. Dawid,et al. Maximum Likelihood Estimation of Observer Error‐Rates Using the EM Algorithm , 1979 .
[51] Jianqing Fan,et al. Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties , 2001 .
[52] Aditya G. Parameswaran,et al. So who won?: dynamic max discovery with the crowd , 2012, SIGMOD Conference.
[53] Qingming Huang,et al. Random partial paired comparison for subjective video quality assessment via hodgerank , 2011, ACM Multimedia.
[54] Gregory N. Hullender,et al. Learning to rank using gradient descent , 2005, ICML.
[55] Xiaochun Cao,et al. False Discovery Rate Control and Statistical Quality Assessment of Annotators in Crowdsourced Ranking , 2016, ICML.