151 citations · 401 across the 21 of their papers we have counts for
6 papers · 1 filter
HodgeRank with Information Maximization for Crowdsourced Pairwise Ranking Aggregation
Qianqian Xu, Jiechao Xiong, Xi Chen +2
Recently, crowdsourcing has emerged as an effective paradigm for human-powered large scale problem solving in various domains. However, task requester usually has a limited amount…
Stochastic Non-convex Ordinal Embedding with Stabilized Barzilai-Borwein Step Size
Ke Ma, Jinshan Zeng, Jiechao Xiong +4
Learning representation from relative similarity comparisons, often called ordinal embedding, gains rising attention in recent years. Most of the existing methods are batch methods…
Exploring Outliers in Crowdsourced Ranking for QoE
Qianqian Xu, Ming Yan, Chendi Huang +3
Outlier detection is a crucial part of robust evaluation for crowdsourceable assessment of Quality of Experience (QoE) and has attracted much attention in recent years. In this pap…
Boosting with Structural Sparsity: A Differential Inclusion Approach
Chendi Huang, Xinwei Sun, Jiechao Xiong +1
Boosting as gradient descent algorithms is one popular method in machine learning. In this paper a novel Boosting-type algorithm is proposed based on restricted gradient descent wi…
False Discovery Rate Control and Statistical Quality Assessment of Annotators in Crowdsourced Ranking
Qianqian Xu, Jiechao Xiong, Xiaochun Cao +1
With the rapid growth of crowdsourcing platforms it has become easy and relatively inexpensive to collect a dataset labeled by multiple annotators in a short time. However due to t…
Analysis of Crowdsourced Sampling Strategies for HodgeRank with Sparse Random Graphs
Braxton Osting, Jiechao Xiong, Qianqian Xu +1
Crowdsourcing platforms are now extensively used for conducting subjective pairwise comparison studies. In this setting, a pairwise comparison dataset is typically gathered via ran…